Robust linear regression methods in association studies

Measurement of ureteral length: Comparison of deep learning-based method and other estimation methods on CT and KUB

BACKGROUND

Accurate preoperative assessment of ureteral length is crucial for effective ureteral stenting.

PURPOSE

Utilize a deep learning approach to measure ureter length on CT urography (CTU) images and compare the obtained results with those derived from other estimation methods.

METHODS

In a retrospective cohort (cohort A, n = 411), CTU images were collected and used to develop a 3D deep learning model for the segmentation of bilateral ureters. The centerline of the ureters was determined based on the segmentation, and the length of the ureters was automatically obtained (CTU_ai). Another cohort (cohort B, n = 220) was collected as the hold-out test for the model. All patients in cohort B had KUB, non-contrast enhanced CT (CT NoC), and CTU images. Cohort B utilized eight measurement methods, with one annotated by two radiologists serving as the reference standard (CTU_ref) and the remaining seven as the studied methods, including three measurement methods applied to CTU (CTU_ai, CTU_oblique, CTU_slice), two applied to CT NoC (CT_oblique, CT_slice), and two applied to KUB (KUB_short, KUB_long). The results of the seven studied methods were compared to those of the reference in cohort B.

RESULTS

Among the 220 patients (96 females, 124 males), 437 ureters were measured for length (218 left, 219 right), with a median length of 24.7 (IQR 23.2-26.2) cm. No significant differences were observed between genders or laterality (both P > 0.05). Moreover, there was no correlation between ureteral length and age (r = -0.027, P = 0.573). The ureteral length measured by CTU_ai was not significantly different from that measured by CTU_ref (P = 0.514), whereas the length measured by the other studied methods was significantly different from that measured by CTU_ref (all P < 0.001). The ICC values with their 95 % confidence intervals (CIs) for the comparison between the reference standard (CTU_ref) and the other measurement methods: CTU_ai (ICC = 0.852, 95 % CI 0.825-0.876), CTU_oblique (ICC = 0.351, 95 % CI -0.083-0.689), CTU_slice (ICC = 0.269, 95 % CI -0.095-0.573), CTU_oblique_slice (ICC = 0.059, 95 % CI -0.032-0.218), CTU_slice (ICC = 0.049, 95 % CI -0.028-0.188), KUB_short (ICC = 0.151, 95 % CI 0.051-0.247), and KUB_long (ICC = 0.147, 95 % CI 0.034-0.253). For CTU_ai, in 89.0 % of the ureters, the ureteral length deviation was within 20 mm of the reference standard, which was the highest among all the studied methods (all P < 0.001).

CONCLUSION

The deep learning model offers a reliable and accurate tool for ureteral length measurement on CTU images, which could enhance the effectiveness of ureteral stenting procedures. Its performance surpasses traditional measurement methods, making it a promising technology for integration into clinical practice.

Maternal pre-pregnancy BMI influences the associations between bisphenol and phthalate exposures and maternal weight changes and fat accumulation

BACKGROUND

Bisphenols and phthalates are two classes of endocrine-disrupting chemicals (EDCs) thought to influence weight and adiposity. Limited research has investigated their influence on maternal weight changes, and no prior work has examined maternal fat mass. We examined the associations between exposure to these chemicals during pregnancy and multiple maternal weight and fat mass outcomes.

METHODS

This study included a sample of 318 women enrolled in a Canadian prospective pregnancy cohort. Second trimester urinary concentrations of 2 bisphenols and 12 phthalate metabolites were quantified. Self-reported and measured maternal weights and measured skinfold thicknesses were used to calculate gestational weight gain, 3-months and 3- to 5-years postpartum weight retention, late pregnancy fat mass gain, total postpartum fat mass loss, and late postpartum fat mass retention. Adjusted robust regressions examined associations between chemicals and outcomes in the entire study population and sub-groups stratified by pre-pregnancy body mass index (BMI). Bayesian kernel machine regression examined chemical mixture effects.

RESULTS

Among women with underweight or normal pre-pregnancy BMIs, MBzP was negatively associated with weight retention at 3- to 5-years postpartum (B = -0.04, 95%CI: -0.07, -0.01). Among women with overweight or obese pre-pregnancy BMIs, MEHP and MMP were positively associated with weight retention at 3-months and 3- to 5-years postpartum, respectively (B's = 0.12 to 0.63, 95%CIs: 0.02, 1.07). DEHP metabolites and MCNP were positively associated with late pregnancy fat mass gain and late postpartum fat mass retention (B's = 0.04 to 0.18, 95%CIs: 0.001, 0.32). Further, the mixture of EDCs was positively associated with late pregnancy fat mass gain.

CONCLUSION

In this cohort, pre-pregnancy BMI was a key determinant of the associations between second trimester exposure to bisphenols and phthalates and maternal weight changes and fat accumulation. Investigations of underlying physiological mechanisms, windows of susceptibility, and impacts on maternal and infant health are needed.

A novel application of data-consistent inversion to overcome spurious inference in genome-wide association studies

The genome-wide association studies (GWAS) typically use linear or logistic regression models to identify associations between phenotypes (traits) and genotypes (genetic variants) of interest. However, the use of regression with the additive assumption has potential limitations. First, the normality assumption of residuals is the one that is rarely seen in practice, and deviation from normality increases the Type-I error rate. Second, building a model based on such an assumption ignores genetic structures, like, dominant, recessive, and protective-risk cases. Ignoring genetic variants may result in spurious conclusions about the associations between a variant and a trait. We propose an assumption-free model built upon data-consistent inversion (DCI), which is a recently developed measure-theoretic framework utilized for uncertainty quantification. This proposed DCI-derived model builds a nonparametric distribution on model inputs that propagates to the distribution of observed data without the required normality assumption of residuals in the regression model. This characteristic enables the proposed DCI-derived model to cover all genetic variants without emphasizing on additivity of the classic-GWAS model. Simulations and a replication GWAS with data from the COPDGene demonstrate the ability of this model to control the Type-I error rate at least as well as the classic-GWAS (additive linear model) approach while having similar or greater power to discover variants in different genetic modes of transmission.

Attentional development is altered in toddlers with congenital heart disease

Background

Congenital Heart Disease (CHD) is the most common congenital abnormality. Survival rates are over 90%, however infants with CHD remain at high risk of attention and executive function impairments. These abilities are difficult to assess in toddlers because clinical assessments rely on language abilities which are commonly delayed in CHD. Our aim was to characterise visual attention in toddlers with CHD compared to controls and identify associations with parent-rated effortful control.

Methods

Thirty toddlers with CHD (19 male, median (IQR) age at assessment 22.2 (22-23.1) months) and 66 controls from the developing human connectome project (36 male, age at assessment 22 (21.5-23.8) months) using eye-tracking tasks designed to assess multiple components of visual attention. Analyses of co-variance and regressions were used to identify differences between groups and relationships between gaze behaviours and parent-rated effortful control.

Results

Toddlers with CHD were less accurate when switching behaviours (set-shifting) [median (IQR) 79%, (28-100)] compared to controls [100% (86-100), pFDR = 0.032], with worse accuracy associated with lower parent-rated effortful control in CHD but not controls (interaction pFDR = 0.028). Reaction times were slower during selective [CHD 1243 ms (986-1786), controls 1065 ms (0851-1397), pFDR<0.001] and exogenous attention tasks [CHD 312 ms (279-358), control 289 (249-331), (pFDR = 0.032) and endogenous attention was less mature (prolonged looks at facial stimuli CHD 670 ms (518-885), control 500 ms (250-625), (pFDR = 0.006). These results were unrelated to differences in cognition or socioeconomic status. In contrast, the allocation of attentional resources was preserved in CHD.

Conclusions

We identified a profile of altered attention and early executive functioning development in CHD. Eye-tracking may provide clinically feasible, early objective measures of attention and executive function development in CHD.

Sex-Specific Associations between Prenatal Exposure to Bisphenols and Phthalates and Infant Epigenetic Age Acceleration

We examined whether prenatal exposure to two classes of endocrine-disrupting chemicals (EDCs) was associated with infant epigenetic age acceleration (EAA), a DNA methylation biomarker of aging. Participants included 224 maternal-infant pairs from a Canadian pregnancy cohort study. Two bisphenols and 12 phthalate metabolites were measured in maternal second trimester urines. Buccal epithelial cell cheek swabs were collected from 3 month old infants and DNA methylation was profiled using the Infinium MethylationEPIC BeadChip. The Pediatric-Buccal-Epigenetic tool was used to estimate EAA. Sex-stratified robust regressions examined individual chemical associations with EAA, and Bayesian kernel machine regression (BKMR) examined chemical mixture effects. Adjusted robust models showed that in female infants, prenatal exposure to total bisphenol A (BPA) was positively associated with EAA (B = 0.72, 95% CI: 0.21, 1.24), and multiple phthalate metabolites were inversely associated with EAA (Bs from -0.36 to -0.66, 95% CIs from -1.28 to -0.02). BKMR showed that prenatal BPA was the most important chemical in the mixture and was positively associated with EAA in both sexes. No overall chemical mixture effects or male-specific associations were noted. These findings indicate that prenatal EDC exposures are associated with sex-specific deviations in biological aging, which may have lasting implications for child health and development.

Attention and motor profiles in children with developmental coordination disorder: A neuropsychological and neuroimaging investigation

AIM

This study aimed to (1) quantify attention and executive functioning in children with developmental coordination disorder (DCD), (2) assess whether some children with DCD are more likely to show attention difficulties, and (3) characterize brain correlates of motor and attention deficits.

METHOD

Fifty-three children (36 with DCD and 17 without) aged 8 to 10 years underwent T1-weighted and diffusion-weighted magnetic resonance imaging, and standardized attention and motor assessments. Parents completed questionnaires of executive functioning and symptoms of inattention and hyperactivity. We assessed regional cortical thickness and surface area, and cerebellar, callosal, and primary motor tract structure.

RESULTS

Analyses of covariance and one-sample t-tests identified impaired attention, non-motor processing speed, and executive functioning in children with DCD, yet partial Spearman's rank correlation coefficients revealed these were unrelated to one another or the type or severity of the motor deficit. Robust regression analyses revealed that cortical morphology in the posterior cingulate was associated with both gross motor skills and inattentive symptoms in children with DCD, while gross motor skills were also associated with left corticospinal tract (CST) morphology.

INTERPRETATION

Children with DCD may benefit from routine attention and hyperactivity assessments. Alterations in the posterior cingulate and CST may be linked to impaired forward modelling during movements in children with DCD. Overall, alterations in these regions may explain the high rate of non-motor impairments in children with DCD.

WHAT THIS PAPER ADDS

Children with developmental coordination disorder have difficulties in attention, processing speed, and executive functioning. Non-motor impairments were not interrelated or correlated with the type or severity of motor deficit. Posterior cingulate morphology was associated with gross motor skills and inattention. Gross motor skills were also associated with left corticospinal tract morphology.

Sex-Specific Associations between Prenatal Exposure to Di(2-ethylhexyl) Phthalate, Epigenetic Age Acceleration, and Susceptibility to Early Childhood Upper Respiratory Infections

Di(2-ethylhexyl) phthalate (DEHP) is a common plasticizer that can affect immune system development and susceptibility to infection. Aging processes (measured as epigenetic age acceleration (EAA)) may mediate the immune-related effects of prenatal exposure to DEHP. This study's objective was to examine associations between prenatal DEHP exposure, EAA at three months of age, and the number of upper respiratory infections (URIs) from 12 to 18 months of age using a sample of 69 maternal-child pairs from a Canadian pregnancy cohort. Blood DNA methylation data were generated using the Infinium HumanMethylation450 BeadChip; EAA was estimated using Horvath's pan-tissue clock. Robust regressions examined overall and sex-specific associations. Higher prenatal DEHP exposure (B = 6.52, 95% CI = 1.22, 11.81) and increased EAA (B = 2.98, 95% CI = 1.64, 4.32) independently predicted more URIs. In sex-specific analyses, some similar effects were noted for boys, and EAA mediated the association between prenatal DEHP exposure and URIs. In girls, higher prenatal DEHP exposure was associated with decreased EAA, and no mediation was noted. Higher prenatal DEHP exposure may be associated with increased susceptibility to early childhood URIs, particularly in boys, and aging biomarkers such as EAA may be a biological mechanism. Larger cohort studies examining the potential developmental immunotoxicity of phthalates are needed.

Cognition in soccer and futsal: evidence of validity of a 4-instrument protocol to assess executive functioning among women athletes

Evidence suggests that success in sports, especially soccer and futsal are linked to higher levels of executive functioning. Still, the literature does not present a homogeneous set of instruments to measure executive functions, which leads to large variability in results. In this paper, we assembled four already recognised measures to propose a valid 4-instrument protocol to assess executive functions among soccer and futsal athletes. We conducted two studies to validate the proposed protocol. We addressed known-groups validity and latent structure in Study 1 for data collected on 105 female soccer and futsal athletes from elite and lower-division clubs. Findings pointed to partial validity of the protocol - with working memory and inhibition showing the best results. For Study 2, we used performance data from 51 elite female soccer players collected throughout a season of the first division league to assess predictive validity. Our protocol was able to partially replicate previous findings and added new insights on how working memory, processing speed and higher-level executive functions might play different roles for goalscoring and assist-making skills. Specifically, study 1 did not find a significant difference between elite and lower-division athletes in higher-order executive functions as in previous studies, but it did find on visual working memory and inhibitory control which weights towards higher demands of core executive functions. On the other hand, study 2 yielded significant results for processing speed and visual working memory to predict assists among elite soccer players, but not inhibitory control as previous findings suggested. Regardless, the proposed 4-instrument protocol showed adequate criterion and structural validity in both studies.

Maternal Pre-Pregnancy BMI and Gestational Weight Gain Are Associated with Preschool Children's Neuropsychological Outcomes in the APrON Cohort

This study examined the associations between maternal pre-pregnancy BMI and gestational weight gain (GWG) and children's neuropsychological outcomes at 3 to 5 years of age. A total of 379 women and their children from the Alberta Pregnancy Outcomes and Nutrition (APrON) study participated. Covariate-adjusted robust regressions examined associations between maternal pre-pregnancy BMI, GWG class, interaction terms, and child outcomes. Each unit increase in maternal BMI was linked to a 0.48-point decrement (95% CI: -0.75 to -0.21) in children's Full Scale IQ. Higher pre-pregnancy BMI was related to poorer performance on the other intelligence indexes (B = -0.35 to -0.47, 95% CIs: -0.75, -0.02) and lower performance on measures of language (B = -0.08 to -0.09, 95% CIs: -0.16, -0.02), motor skills (B = -0.08 to -0.11, 95% CIs: -0.18, -0.01), and executive function (B = -0.09 to -0.16, 95% CIs: -0.26, -0.01). GWG below the recommended range was associated with a 4.04-point decrement (95% CI: 7.89, -0.11) in Full Scale IQ, but better performance on a spatial working memory test (B = 0.27, 95% CI: 0.02, 0.52). GWG above the recommended range was associated with lower language (B = -0.79, 95% CI: -1.52, -0.06) and memory scores (B = -0.93, 95% CI: -1.64, -0.22). Interactions were found between pre-pregnancy BMI and GWG on measures of intelligence and executive function. Maternal pre-pregnancy BMI and GWG are related to children's performance in various neuropsychological domains and may interact to predict outcomes. Optimizing maternal health and weight prior to conception and during pregnancy may enhance children's neuropsychological outcomes.

Sex-specific associations between maternal phthalate exposure and neurodevelopmental outcomes in children at 2 years of age in the APrON cohort

BACKGROUND

There is inconsistent evidence regarding the sex-specific associations between prenatal phthalate exposure and children's neurodevelopment. This could be due to differences in the phthalate exposures investigated and the neurodevelopmental domains assessed.

OBJECTIVE

To evaluate the associations between prenatal phthalate exposure and sex-specific outcomes on measures of cognition, language, motor, executive function, and behaviour in children 2 years of age in the Alberta Pregnancy Outcomes and Nutrition (APrON) cohort.

METHODS

We evaluated the associations between prenatal phthalate exposure and sex-specific neurodevelopmental outcomes in children at 2 years of age using data from 448 mothers and their children (222 girls, 226 boys). Nine phthalate metabolites were measured in maternal urine collected in the second trimester of pregnancy. Children's cognitive, language, and motor outcomes were assessed using the Bayley Scales of Infant Development - Third Edition (Bayley-III). Parents completed questionnaires on children's executive function and behavior, the Behavior Rating Inventory of Executive Function- Preschool Version (BRIEF-P) and Child Behavior Checklist (CBCL), respectively. Sex-stratified robust multivariate regressions were performed.

RESULTS

Higher maternal concentrations of ΣDEHP and its metabolites were associated with lower scores on the Bayley-III Cognitive (β's from -11.8 to -0.07 95% CI's from -21.3 to -0.01), Language (β's from -11.7 to -0. 09, 95% CI's from -22.3 to -0.02) and Motor (β's from -10.9 to -0.07, 95% CI from -20.4 to -0.01) composites in boys. The patterns of association in girls were in the opposite direction on the Cognitive and Language composites; on the Motor composite they were in the same direction as boys, but of reduced strength. Higher concentrations of ΣDEHP and its metabolites were associated with higher scores (i.e., more difficulties) on all measures of executive function in girls: inhibitory self-control (B's from 0.05 to 0.11, 95% CI s from -0.01 to 0.15), flexibility (B's from 0.04 to 0.11, 95% CI s from 0.01 to 0.21) and emergent metacognition (B's from -0.01 to 0.06, 95% CIs from -0.01 to 0.20). Similar patterns of attenuated associations were seen in boys. Higher concentrations of ΣDEHP and its metabolites were associated with more Externalizing Problems in girls and boys (B's from 0.03 to 6.82, 95% CIs from -0.08 to 12.0). Two phthalates, MMP and MBP, had sex-specific adverse associations on measures of executive function and behaviour, respectively, while MEP was positively associated with boys' cognitive, language, and motor performance. Limited associations were observed between mixtures of maternal phthalates and sex-specific neurodevelopmental outcomes.

CONCLUSIONS

Maternal prenatal concentrations of DEHP phthalates were associated with sex specific difference on measures of cognition and language at 2 years of age, specifically, poorer outcomes in boys. Higher exposure to DEHP was associated with poorer motor, executive function, and behavioural outcomes in girls and boys but the strength of these associations differed by sex. Limited associations were noted between phthalate mixtures and child neurodevelopment.

Maternal depressive symptoms, neonatal white matter, and toddler social-emotional development

Maternal prenatal depression is associated with increased likelihood of neurodevelopmental and psychiatric conditions in offspring. The relationship between maternal depression and offspring outcome may be mediated by in-utero changes in brain development. Recent advances in magnetic resonance imaging (MRI) have enabled in vivo investigations of neonatal brains, minimising the effect of postnatal influences. The aim of this study was to examine associations between maternal prenatal depressive symptoms, infant white matter, and toddler behaviour. 413 mother-infant dyads enrolled in the developing Human Connectome Project. Mothers completed the Edinburgh Postnatal Depression Scale (median = 5, range = 0-28, n = 52 scores ≥ 11). Infants (n = 223 male) (median gestational age at birth = 40 weeks, range 32.14-42.29) underwent MRI (median postmenstrual age at scan = 41.29 weeks, range 36.57-44.71). Fixel-based fibre metrics (mean fibre density, fibre cross-section, and fibre density modulated by cross-section) were calculated from diffusion imaging data in the left and right uncinate fasciculi and cingulum bundle. For n = 311, internalising and externalising behaviour, and social-emotional abilities were reported at a median corrected age of 18 months (range 17-24). Statistical analysis used multiple linear regression and mediation analysis with bootstrapping. Maternal depressive symptoms were positively associated with infant fibre density in the left (B = 0.0005, p = 0.003, q = 0.027) and right (B = 0.0006, p = 0.003, q = 0.027) uncinate fasciculus, with left uncinate fasciculus fibre density, in turn, positively associated with social-emotional abilities in toddlerhood (B = 105.70, p = 0.0007, q = 0.004). In a mediation analysis, higher maternal depressive symptoms predicted toddler social-emotional difficulties (B = 0.342, t(307) = 3.003, p = 0.003), but this relationship was not mediated by fibre density in the left uncinate fasciculus (Sobel test p = 0.143, bootstrapped indirect effect = 0.035, SE = 0.02, 95% CI: [-0.01, 0.08]). There was no evidence of an association between maternal depressive and cingulum fibre properties. These findings suggest that maternal perinatal depressive symptoms are associated with neonatal uncinate fasciculi microstructure, but not fibre bundle size, and toddler behaviour.

Prenatal exposure to phthalates and peripheral blood and buccal epithelial DNA methylation in infants: An epigenome-wide association study

BACKGROUND

Prenatal exposure to phthalates has been associated with adverse health and neurodevelopmental outcomes. DNA methylation (DNAm) alterations may be a mechanism underlying these effects, but prior investigations of prenatal exposure to phthalates and neonatal DNAm profiles are limited to placental tissue and umbilical cord blood.

OBJECTIVE

Conduct an epigenome-wide association study (EWAS) of the associations between prenatal exposure to phthalates and DNAm in two accessible infant tissues, venous buffy coat blood and buccal epithelial cells (BECs).

METHODS

Participants included 152 maternal-infant pairs from the Alberta Pregnancy Outcomes and Nutrition (APrON) study. Maternal second trimester urine samples were analyzed for nine phthalate metabolites. Blood (n = 74) or BECs (n = 78) were collected from 3-month-old infants and profiled for DNAm using the Infinium HumanMethylation450 (450K) BeadChip. Robust linear regressions were used to investigate the associations between high (HMWPs) and low molecular weight phthalates (LMWPs) and change in methylation levels at variable Cytosine-phosphate-Guanine (CpG) sites in infant tissues, as well as the sensitivity of associations to potential confounders.

RESULTS

One candidate CpG in gene RNF39 reported by a previous study examining prenatal exposure to phthalates and cord blood DNAm was replicated. The EWAS identified 12 high-confidence CpGs in blood and another 12 in BECs associated with HMWPs and/or LMWPs. Prenatal exposure to bisphenol A (BPA) associated with two of the CpGs associated with HMWPs in BECs.

DISCUSSION

Prenatal exposure to phthalates was associated with DNAm variation at CpGs annotated to genes associated with endocrine hormone activity (i.e., SLCO4A1, TPO), immune pathways and DNA damage (i.e., RASGEF1B, KAZN, HLA-A, MYO18A, DIP2C, C1or109), and neurodevelopment (i.e., AMPH, NOTCH3, DNAJC5). Future studies that characterize the stability of these associations in larger samples, multiple cohorts, across tissues, and investigate the potential associations between these biomarkers and relevant health and neurodevelopmental outcomes are needed.

Satiety does not alter the ventral striatum's response to immediate reward in bulimia nervosa

Individuals with bulimia nervosa (BN) cycle between periods of binge-eating and compensatory behavior and periods of dietary restraint, suggesting extremes of under and overcontrol that may be metabolic-state related. This study examined the influence of hunger and satiety on impulsivity and neural responding during decision-making. Twenty-three women remitted from BN (RBN) and 20 healthy comparison women (CW) performed a delay discounting task after a 16-hr fast and following a standardized meal during functional neuroimaging. A dual-systems approach examined reward valuation (decision trials where the early reward option was available immediately) and cognitive control (all decision trials). Interactions of Group × Visit (Hungry, Fed) for immediate reward revealed that CW had greater activation when hungry versus fed in the ventral striatum and dorsal caudate, whereas RBN had greater response when fed versus hungry in the dorsal caudate. Compared to CW, RBN showed decreased response when hungry within the left dorsal caudate and ventral striatum and increased response when fed in bilateral dorsal caudate. No differences were found within cognitive control regions or with choice behavior. Reward sensitivity is normally increased when hungry and decreased when fed; our findings in CW provide further support of hunger-based reward sensitivity within the striatum. However, RBN showed no differences for hunger and satiety in the ventral striatum and greater activation in the dorsal caudate when fed compared to hungry. This suggests RBN may be less sensitive to reward when hungry but do not devalue reward when satiated, indicating altered metabolic modulation of self-regulatory control. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Genomics of Postprandial Lipidomics in the Genetics of Lipid-Lowering Drugs and Diet Network Study

Postprandial lipemia (PPL) is an important risk factor for cardiovascular disease. Inter-individual variation in the dietary response to a meal is known to be influenced by genetic factors, yet genes that dictate variation in postprandial lipids are not completely characterized. Genetic studies of the plasma lipidome can help to better understand postprandial metabolism by isolating lipid molecular species which are more closely related to the genome. We measured the plasma lipidome at fasting and 6 h after a standardized high-fat meal in 668 participants from the Genetics of Lipid-Lowering Drugs and Diet Network study (GOLDN) using ultra-performance liquid chromatography coupled to (quadrupole) time-of-flight mass spectrometry. A total of 413 unique lipids were identified. Heritable and responsive lipid species were examined for association with single-nucleotide polymorphisms (SNPs) genotyped on the Affymetrix 6.0 array. The most statistically significant SNP findings were replicated in the Amish Heredity and Phenotype Intervention (HAPI) Heart Study. We further followed up findings from GOLDN with a regional analysis of cytosine-phosphate-guanine (CpGs) sites measured on the Illumina HumanMethylation450 array. A total of 132 lipids were both responsive to the meal challenge and heritable in the GOLDN study. After correction for multiple testing of 132 lipids (α = 5 × 10-8/132 = 4 × 10-10), no SNP was statistically significantly associated with any lipid response. Four SNPs in the region of a known lipid locus (fatty acid desaturase 1 and 2/FADS1 and FADS2) on chromosome 11 had p < 8.0 × 10-7 for arachidonic acid FA(20:4). Those SNPs replicated in HAPI Heart with p < 3.3 × 10-3. CpGs around the FADS1/2 region were associated with arachidonic acid and the relationship of one SNP was partially mediated by a CpG (p = 0.005). Both SNPs and CpGs from the fatty acid desaturase region on chromosome 11 contribute jointly and independently to the diet response to a high-fat meal.

An Integrative Analysis of Transcriptome and GWAS Data to Identify Potential Candidate Genes Influencing Meat Quality Traits in Pigs

Understanding the genetic factors behind meat quality traits is of great significance to animal breeding and production. We previously conducted a genome-wide association study (GWAS) for meat quality traits in a White Duroc × Erhualian F2 pig population using Illumina porcine 60K SNP data. Here, we further investigate the functional candidate genes and their network modules associated with meat quality traits by integrating transcriptomics and GWAS information. Quantitative trait transcript (QTT) analysis, gene expression QTL (eQTL) mapping, and weighted gene co-expression network analysis (WGCNA) were performed using the digital gene expression (DGE) data from 493 F2 pig's muscle and liver samples. Among the quantified 20,108 liver and 23,728 muscle transcripts, 535 liver and 1,014 muscle QTTs corresponding to 416 and 721 genes, respectively, were found to be significantly (p < 5 × 10^-4) correlated with 22 meat quality traits measured on longissiums dorsi muscle (LM) or semimembranosus muscle (SM). Transcripts associated with muscle glycolytic potential (GP) and pH values were enriched for genes involved in metabolic process. There were 42 QTTs (for 32 genes) shared by liver and muscle tissues, of which 10 QTTs represent GP- and/or pH-related genes, such as JUNB, ATF3, and PPP1R3B. Furthermore, a genome-wide eQTL mapping revealed a total of 3,054 eQTLs for all annotated transcripts in muscle (p < 2.08 × 10^-5), including 1,283 cis-eQTLs and 1771 trans-eQTLs. In addition, WGCNA identified five modules relevant to glycogen metabolism pathway and highlighted the connections between variations in meat quality traits and genes involved in energy process. Integrative analysis of GWAS loci, eQTL, and QTT demonstrated GALNT15/GALNTL2 and HTATIP2 as strong candidate genes for drip loss and pH drop from postmortem 45 min to 24 h, respectively. Our findings provide valuable insights into the genetic basis of meat quality traits and greatly expand the number of candidate genes that may be valuable for future functional analysis and genetic improvement of meat quality.

Seasonal weather and climate prediction over area burned in grasslands of northeast China

Grassland fire dynamics are subject to myriad climatic, biological, and anthropogenic drivers, thresholds, and feedbacks and therefore do not conform to assumptions of statistical stationarity. The presence of non-stationarity in time series data leads to ambiguous results that can misinform regional-level fire management strategies. This study employs non-stationarity in time series data among multiple variables and multiple intensities using dynamic simulations of autoregressive distributed lag models to elucidate key drivers of climate and ecological change on burned grasslands in Xilingol, China. We used unit root methods to select appropriate estimation methods for further analysis. Using the model estimations, we developed scenarios emulating the effects of instantaneous changes (i.e., shocks) of some significant variables on climate and ecological change. Changes in mean monthly wind speed and maximum temperature produce complex responses on area burned, directly, and through feedback relationships. Our framework addresses interactions among multiple drivers to explain fire and ecosystem responses in grasslands, and how these may be understood and prioritized in different empirical contexts needed to formulate effective fire management policies.

Robust estimation of heritability and predictive accuracy in plant breeding: evaluation using simulation and empirical data

BACKGROUND

Genomic prediction (GP) is used in animal and plant breeding to help identify the best genotypes for selection. One of the most important measures of the effectiveness and reliability of GP in plant breeding is predictive accuracy. An accurate estimate of this measure is thus central to GP. Moreover, regression models are the models of choice for analyzing field trial data in plant breeding. However, models that use the classical likelihood typically perform poorly, often resulting in biased parameter estimates, when their underlying assumptions are violated. This typically happens when data are contaminated with outliers. These biases often translate into inaccurate estimates of heritability and predictive accuracy, compromising the performance of GP. Since phenotypic data are susceptible to contamination, improving the methods for estimating heritability and predictive accuracy can enhance the performance of GP. Robust statistical methods provide an intuitively appealing and a theoretically well justified framework for overcoming some of the drawbacks of classical regression, most notably the departure from the normality assumption. We compare the performance of robust and classical approaches to two recently published methods for estimating heritability and predictive accuracy of GP using simulation of several plausible scenarios of random and block data contamination with outliers and commercial maize and rye breeding datasets.

RESULTS

The robust approach generally performed as good as or better than the classical approach in phenotypic data analysis and in estimating the predictive accuracy of heritability and genomic prediction under both the random and block contamination scenarios. Notably, it consistently outperformed the classical approach under the random contamination scenario. Analyses of the empirical maize and rye datasets further reinforce the stability and reliability of the robust approach in the presence of outliers or missing data.

CONCLUSIONS

The proposed robust approach enhances the predictive accuracy of heritability and genomic prediction by minimizing the deleterious effects of outliers for a broad range of simulation scenarios and empirical breeding datasets. Accordingly, plant breeders should seriously consider regularly using the robust alongside the classical approach and increasing the number of replicates to three or more, to further enhance the accuracy of the robust approach.

A robust Bayesian genome-based median regression model

Current genome-enabled prediction models assumed errors normally distributed, which are sensitive to outliers. We propose a model with errors assumed to follow a Laplace distribution to deal better with outliers. Current genome-enabled prediction models use regressions that fit the expected value (mean) of a response variable with errors assumed normally distributed, which are often sensitive to outliers, either genetic or environmental. For this reason, we propose a robust Bayesian genome median regression (BGMR) model that fits regressions to the medians of a distribution, with errors assumed to follow a Laplace distribution to deal better with outliers. The BGMR model was evaluated under a Bayesian framework with Markov Chain Monte Carlo sampling using a location-scale mixture representation of the Laplace distribution. The BGMR was implemented with two simulated and two real genomic data sets, and we compared its prediction performance with that of a conventional genomic best linear unbiased prediction (GBLUP) model and the Laplace maximum a posteriori (LMAP) method. The prediction accuracies of BGMR were higher than those of the GBLUP and LMAP methods when there were outliers. The BGMR model could be useful to breeders who need to predict and select genotypes based on data with unknown outliers.

Copy number variation in the MSRB3 gene enlarges porcine ear size through a mechanism involving miR-584-5p

Background

The size and type of ears are important conformation characteristics that distinguish pig breeds. A significant quantitative trait locus (QTL) for ear size has been identified on SSC5 (SSC for Sus scrofa chromosome) but the underlying causative gene and mutation remain unknown. Thus, our aim was to identify the gene responsible for enlarged ears in pig.

Results

First, we narrowed down the QTL region on SSC5 to a 137.85-kb interval that harbors only the methionine sulfoxide reductase B3 (MSRB3) gene. Then, we identified a 38.7-kb copy number variation (CNV) that affects the last two exons of MSRB3 and could be the candidate causative mutation for this QTL. This CNV showed complete concordance with genotype at the QTL of the founder animals in a white Duroc × Erhualian F₂ intercross and was found only in pigs from six Chinese indigenous breeds with large ears and from the Landrace breed with half-floppy ears. Moreover, it accounted for the significant association with ear size on SSC5 across the five pig populations tested. eQTL mapping revealed that this CNV was significantly associated with the expression of the microRNA (miRNA) miR-584-5p, which interacts with MSRB3, one of its target genes. In vivo and in vitro experiments confirmed that miR-584-5p inhibits the translation of MSRB3 mRNA. Taken together, these results led us to conclude that presence of the 38.7-kb CNV in the genome of some pig breeds affects ear size by altering the expression of miR-584-5p, which consequently hinders the expression of one of its target genes (e.g. MSRB3).

Conclusions

Our findings shed insight into the underlying mechanism of development of external ears in mammals and contribute to a better understanding of how the presence of CNV can regulate gene expression.

Electronic supplementary material

The online version of this article (10.1186/s12711-018-0442-6) contains supplementary material, which is available to authorized users.

A robust DF-REML framework for variance components estimation in genetic studies

Motivation

In genetic association studies, linear mixed models (LMMs) are used to test for associations between phenotypes and candidate single nucleotide polymorphisms (SNPs). These same models are also used to estimate heritability, which is central not only to evolutionary biology but also to the prediction of the response to selection in plant and animal breeding, as well as the prediction of disease risk in humans. However, when one or more of the underlying assumptions are violated, the estimation of variance components may be compromised and therefore so may the estimates of heritability and any other functions of these. Considering that datasets obtained from real life experiments are prone to several sources of contamination, which usually induce the violation of the assumption of the normality of the errors, a robust derivative-free restricted-maximum likelihood framework (DF-REML) together with a robust coefficient of determination are proposed for the LMM in the context of genetic studies of continuous traits.

Results

The proposed approach, in addition to the robust estimation of variance components and robust computation of the coefficient of determination, allows in particular for the robust estimation of SNP-based heritability by reducing the bias and increasing the precision of its estimates. The performance of both classical and robust DF-REML approaches is compared via a Monte Carlo simulation study. Additionally, three examples of application of the methodologies to real datasets are given in order to validate the usefulness of the proposed robust approach. Although the main focus of this article is on plant breeding applications, the proposed methodology is applicable to both human and animal genetic studies.

Availability and implementation

Source code implemented in R is available in the Supplementary Material.

Contact

vmml@fct.unl.pt.

Supplementary information

Supplementary data are available at Bioinformatics online.

Metabolic and inflammatory biomarkers are associated with epigenetic aging acceleration estimates in the GOLDN study

Background

Recently, epigenetic age acceleration-or older epigenetic age in comparison to chronological age-has been robustly associated with mortality and various morbidities. However, accelerated epigenetic aging has not been widely investigated in relation to inflammatory or metabolic markers, including postprandial lipids.

Methods

We estimated measures of epigenetic age acceleration in 830 Caucasian participants from the Genetics Of Lipid Lowering Drugs and diet Network (GOLDN) considering two epigenetic age calculations based on differing sets of 5'-Cytosine-phosphate-guanine-3' genomic site, derived from the Horvath and Hannum DNA methylation age calculators, respectively. GOLDN participants underwent a standardized high-fat meal challenge after fasting for at least 8 h followed by timed blood draws, the last being 6 h postmeal. We used adjusted linear mixed models to examine the association of the epigenetic age acceleration estimate with fasting and postprandial (0- and 6-h time points) low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglyceride (TG) levels as well as five fasting inflammatory markers plus adiponectin.

Results

Both DNA methylation age estimates were highly correlated with chronological age (r > 0.90). We found that the Horvath and Hannum measures of epigenetic age acceleration were moderately correlated (r = 0.50). The regression models revealed that the Horvath age acceleration measure exhibited marginal associations with increased postprandial HDL (p = 0.05), increased postprandial total cholesterol (p = 0.06), and decreased soluble interleukin 2 receptor subunit alpha (IL2sRα, p = 0.02). The Hannum measure of epigenetic age acceleration was inversely associated with fasting HDL (p = 0.02) and positively associated with postprandial TG (p = 0.02), interleukin-6 (IL6, p = 0.007), C-reactive protein (C-reactive protein, p = 0.0001), and tumor necrosis factor alpha (TNFα, p = 0.0001). Overall, the observed effect sizes were small and the association of the Hannum residual with inflammatory markers was attenuated by adjustment for estimated T cell type percentages.

Conclusions

Our study demonstrates that epigenetic age acceleration in blood relates to inflammatory biomarkers and certain lipid classes in Caucasian individuals of the GOLDN study. Future studies should consider epigenetic age acceleration in other tissues and extend the analysis to other ethnic groups.

Epigenome-wide association study of metabolic syndrome in African-American adults

Background

The high prevalence of obesity among US adults has resulted in significant increases in associated metabolic disorders such as diabetes, dyslipidemia, and high blood pressure. Together, these disorders constitute metabolic syndrome, a clinically defined condition highly prevalent among African-Americans. Identifying epigenetic alterations associated with metabolic syndrome may provide additional information regarding etiology beyond current evidence from genome-wide association studies.

Methods

Data on metabolic syndrome and DNA methylation was assessed on 614 African-Americans from the Hypertension Genetic Epidemiology Network (HyperGEN) study. Metabolic syndrome was defined using the joint harmonized criteria, and DNA methylation was assessed using the Illumina HumanMethylation450K Bead Chip assay on DNA extracted from buffy coat. Linear mixed effects regression models were used to examine the association between CpG methylation at > 450,000 CpG sites and metabolic syndrome adjusted for study covariates. Replication using DNA from a separate sample of 69 African-Americans, as well as meta-analysis combining both cohorts, was conducted.

Results

Two differentially methylated CpG sites in the IGF2BP1 gene on chromosome 17 (cg06638433; p value = 3.10 × 10^− 7) and the ABCG1 gene on chromosome 21 (cg06500161; p value = 2.60 × 10^− 8) were identified. Results for the ABCG1 gene remained statistically significant in the replication dataset and meta-analysis.

Conclusion

Metabolic syndrome was consistently associated with increased methylation in the ABCG1 gene in the discovery and replication datasets, a gene that encodes a protein in the ATP-binding cassette transporter family and is involved in intra- and extra-cellular signaling and lipid transport.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0483-2) contains supplementary material, which is available to authorized users.

Genome-wide identification of quantitative trait transcripts for blood traits in the liver samples of a White Duroc × Erhualian F2 pig resource population

Blood cell counts are important clinical indicators for health status. The liver plays a crucial role in food digestion and metabolism and is also a blood-forming organ. Here, we conducted a whole-genome quantitative trait transcript (QTT) analysis on 497 liver samples for 16 hematological traits in a White Duroc × Erhualian F2 pig resource population. A total of 20,108 transcripts were explored to detect their association with hematological traits. By using Spearman correlation coefficients, we identified 1,267 QTTs for these 16 hematological traits at the significance threshold of P < 0.001. We found 31 candidate genes for erythrocyte and leukocyte-related traits by a look-up of human and pig genome-wide association study results. Furthermore, we constructed coexpression networks for leukocyte-related QTTs using weighted gene coexpression analysis. These QTTs were clustered into two to eight modules. The highest connection strength in intramodules was identified in a module for white blood cell count. In the module, USP18, RSAD2, and OAS1 appeared to be important genes involved in interferon-stimulated innate immune system. The findings improve our understanding of intrinsic relationships between the liver and blood cells and provide novel insights into the potential therapeutic targets of hematologic diseases.

A robust AMMI model for the analysis of genotype-by-environment data

MOTIVATION

One of the most widely used models to analyse genotype-by-environment data is the additive main effects and multiplicative interaction (AMMI) model. Genotype-by-environment data resulting from multi-location trials are usually organized in two-way tables with genotypes in the rows and environments (location-year combinations) in the columns. The AMMI model applies singular value decomposition (SVD) to the residuals of a specific linear model, to decompose the genotype-by-environment interaction (GEI) into a sum of multiplicative terms. However, SVD, being a least squares method, is highly sensitive to contamination and the presence of even a single outlier, if extreme, may draw the leading principal component towards itself resulting in possible misinterpretations and in turn lead to bad practical decisions. Since, as in many other real-life studies the distribution of these data is usually not normal due to the presence of outlying observations, either resulting from measurement errors or sometimes from individual intrinsic characteristics, robust SVD methods have been suggested to help overcome this handicap.

RESULTS

We propose a robust generalization of the AMMI model (the R-AMMI model) that overcomes the fragility of its classical version when the data are contaminated. Here, robust statistical methods replace the classic ones to model, structure and analyse GEI. The performance of the robust extensions of the AMMI model is assessed through a Monte Carlo simulation study where several contamination schemes are considered. Applications to two real plant datasets are also presented to illustrate the benefits of the proposed methodology, which can be broadened to both animal and human genetics studies.

AVAILABILITY AND IMPLEMENTATION

Source code implemented in R is available in the supplementary material under the function r-AMMI.

CONTACT

paulocanas@gmail.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification of quantitative trait transcripts for growth traits in the large scales of liver and muscle samples

Growth-related traits are economically important traits to the pig industry. Identification of causative gene and mutation responsible for growth-related QTL will facilitate the improvement of pig growth through marker-assisted selection. In this study, we applied whole genome gene expression and quantitative trait transcript (QTT) analyses in 497 liver and 586 longissimus dorsi muscle samples to identify candidate genes and dissect the genetic basis of pig growth in a white Duroc × Erhualian F2 resource population. A total of 20,108 transcripts in liver and 23,728 transcripts in muscle with expression values were used for association analysis between gene expression level and phenotypic value. At the significance threshold of P < 0.0005, we identified a total of 169 and 168 QTTs for nine growth-related traits in liver and muscle, respectively. We also found that some QTTs were correlated to more than one trait. The QTTs identified here showed high tissue specificity. We did not identify any QTTs that were associated with one trait in both liver and muscle. Through an integrative genomic approach, we identified SDR16C5 as the important candidate gene in pig growth trait. These findings contribute to further identification of the causative genes for porcine growth traits and facilitate improvement of pig breeding.

Genome-wide epistatic expression quantitative trait loci discovery in four human tissues reveals the importance of local chromosomal interactions governing gene expression

Background

Epistasis (synergistic interaction) among SNPs governing gene expression is likely to arise within transcriptional networks. However, the power to detect it is limited by the large number of combinations to be tested and the modest sample sizes of most datasets. By limiting the interaction search space firstly to cis-trans and then cis-cis SNP pairs where both SNPs had an independent effect on the expression of the most variable transcripts in the liver and brain, we greatly reduced the size of the search space.

Results

Within the cis-trans search space we discovered three transcripts with significant epistasis. Surprisingly, all interacting SNP pairs were located nearby each other on the chromosome (within 290 kb-2.16 Mb). Despite their proximity, the interacting SNPs were outside the range of linkage disequilibrium (LD), which was absent between the pairs (r² < 0.01). Accordingly, we redefined the search space to detect cis-cis interactions, where a cis-SNP was located within 10 Mb of the target transcript. The results of this show evidence for the epistatic regulation of 50 transcripts across the tissues studied. Three transcripts, namely, HLA-G, PSORS1C1 and HLA-DRB5 share common regulatory SNPs in the pre-frontal cortex and their expression is significantly correlated. This pattern of epistasis is consistent with mediation via long-range chromatin structures rather than the binding of transcription factors in trans. Accordingly, some of the interactions map to regions of the genome known to physically interact in lymphoblastoid cell lines while others map to known promoter and enhancer elements. SNPs involved in interactions appear to be enriched for promoter markers.

Conclusions

In the context of gene expression and its regulation, our analysis indicates that the study of cis-cis or local epistatic interactions may have a more important role than interchromosomal interactions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1300-3) contains supplementary material, which is available to authorized users.

A splice mutation in the PHKG1 gene causes high glycogen content and low meat quality in pig skeletal muscle

Glycolytic potential (GP) in skeletal muscle is economically important in the pig industry because of its effect on pork processing yield. We have previously mapped a major quantitative trait loci (QTL) for GP on chromosome 3 in a White Duroc × Erhualian F₂ intercross. We herein performed a systems genetic analysis to identify the causal variant underlying the phenotype QTL (pQTL). We first conducted genome-wide association analyses in the F₂ intercross and an F₁₉ Sutai pig population. The QTL was then refined to an 180-kb interval based on the 2-LOD drop method. We then performed expression QTL (eQTL) mapping using muscle transcriptome data from 497 F₂ animals. Within the QTL interval, only one gene (PHKG1) has a cis-eQTL that was colocolizated with pQTL peaked at the same SNP. The PHKG1 gene encodes a catalytic subunit of the phosphorylase kinase (PhK), which functions in the cascade activation of glycogen breakdown. Deep sequencing of PHKG1 revealed a point mutation (C>A) in a splice acceptor site of intron 9, resulting in a 32-bp deletion in the open reading frame and generating a premature stop codon. The aberrant transcript induces nonsense-mediated decay, leading to lower protein level and weaker enzymatic activity in affected animals. The mutation causes an increase of 43% in GP and a decrease of>20% in water-holding capacity of pork. These effects were consistent across the F₂ and Sutai populations, as well as Duroc × (Landrace × Yorkshire) hybrid pigs. The unfavorable allele exists predominantly in Duroc-derived pigs. The findings provide new insights into understanding risk factors affecting glucose metabolism, and would greatly contribute to the genetic improvement of meat quality in Duroc related pigs.

Glycogen storage diseases (GSD) are a group of inherited disorders characterized by storage of excess glycogen, which are mainly caused by the abnormality of a particular enzyme essential for releasing glucose from glycogen. GSD-like conditions have been described in a wide variety of species. Pigs are a valuable model for the study of human GSD. Moreover, pigs affected by GSD usually produce inferior pork with a lower ultimate pH (so-called “acid meat”) and less processing yield due to post-mortem degradation of the excess glycogen. So far, only one causal variant, PRKAG3 R225Q, has been identified for GSD in pigs. Here we reported a loss-of-function mutation in the PHKG1 gene that causes the deficiency of the glycogen breakdown, consequently leading to GSD and acid meat in Duroc-sired pigs. Eliminating the undesirable mutation from the breeding stock by a diagnostic DNA test will greatly reduce the incidence of GSD and significantly improve pork quality and productivity in the pig.

Genomics of post-prandial lipidomic phenotypes in the Genetics of Lipid lowering Drugs and Diet Network (GOLDN) study

BACKGROUND

Increased postprandial lipid (PPL) response to dietary fat intake is a heritable risk factor for cardiovascular disease (CVD). Variability in postprandial lipids results from the complex interplay of dietary and genetic factors. We hypothesized that detailed lipid profiles (eg, sterols and fatty acids) may help elucidate specific genetic and dietary pathways contributing to the PPL response.

METHODS AND RESULTS

We used gas chromatography mass spectrometry to quantify the change in plasma concentration of 35 fatty acids and 11 sterols between fasting and 3.5 hours after the consumption of a high-fat meal (PPL challenge) among 40 participants from the GOLDN study. Correlations between sterols, fatty acids and clinical measures were calculated. Mixed linear regression was used to evaluate associations between lipidomic profiles and genomic markers including single nucleotide polymorphisms (SNPs) and methylation markers derived from the Affymetrix 6.0 array and the Illumina Methyl450 array, respectively. After the PPL challenge, fatty acids increased as well as sterols associated with cholesterol absorption, while sterols associated with cholesterol synthesis decreased. PPL saturated fatty acids strongly correlated with triglycerides, very low-density lipoprotein, and chylomicrons. Two SNPs (rs12247017 and rs12240292) in the sorbin and SH3 domain containing 1 (SORBS1) gene were associated with b-Sitosterol after correction for multiple testing (P≤4.5*10(-10)). SORBS1 has been linked to obesity and insulin signaling. No other markers reached the genome-wide significance threshold, yet several other biologically relevant loci are highlighted (eg, PRIC285, a co-activator of PPARa).

CONCLUSIONS

Integration of lipidomic and genomic data has the potential to identify new biomarkers of CVD risk.

A meta-analysis of genome-wide association studies for serum total IgE in diverse study populations

BACKGROUND

IgE is both a marker and mediator of allergic inflammation. Despite reported differences in serum total IgE levels by race-ethnicity, African American and Latino subjects have not been well represented in genetic studies of total IgE.

OBJECTIVE

We sought to identify the genetic predictors of serum total IgE levels.

METHODS

We used genome-wide association data from 4292 subjects (2469 African Americans, 1564 European Americans, and 259 Latinos) in the EVE Asthma Genetics Consortium. Tests for association were performed within each cohort by race-ethnic group (ie, African American, Latino, and European American) and asthma status. The resulting P values were meta-analyzed, accounting for sample size and direction of effect. Top single nucleotide polymorphism associations from the meta-analysis were reassessed in 6 additional cohorts comprising 5767 subjects.

RESULTS

We identified 10 unique regions in which the combined association statistic was associated with total serum IgE levels (P<5.0×10(-6)) and the minor allele frequency was 5% or greater in 2 or more population groups. Variant rs9469220, corresponding to HLA-DQB1, was the single nucleotide polymorphism most significantly associated with serum total IgE levels when assessed in both the replication cohorts and the discovery and replication sets combined (P=.007 and 2.45×10(-7), respectively). In addition, findings from earlier genome-wide association studies were also validated in the current meta-analysis.

CONCLUSION

This meta-analysis independently identified a variant near HLA-DQB1 as a predictor of total serum IgE levels in multiple race-ethnic groups. This study also extends and confirms the findings of earlier genome-wide association analyses in African American and Latino subjects.

Lack of association between p53 SNP and FISS in a cat population from Germany

One recent study indicates a significant association between certain single nucleotide polymorphisms (SNPs) in the genomic sequence of feline p53 and feline injection-site sarcoma (FISS). The aim of this study was to investigate the correlation between a specific nucleotide insertion in p53 gene and FISS in a German cat population. Blood samples from 150 German cats were allocated to a control group consisting of 100 healthy cats and a FISS-group consisting of 50 cats with FISS. All blood samples were examined for the presence of the SNP in the p53 gene. Results found the T-insertion at SNP 3 in 20.0% of the cats in the FISS-group and 19.2% of cats in the control-group. No statistically significant difference was observed in allelic distribution between the two groups. Further investigations are necessary to determine the association of SNPs in the feline p53 gene and the occurrence of FISS.

Whole-exome sequencing and an iPSC-derived cardiomyocyte model provides a powerful platform for gene discovery in left ventricular hypertrophy

Rationale: Left ventricular hypertrophy (LVH) is a heritable predictor of cardiovascular disease, particularly in blacks. Objective: Determine the feasibility of combining evidence from two distinct but complementary experimental approaches to identify novel genetic predictors of increased LV mass. Methods: Whole-exome sequencing (WES) was conducted in seven African-American sibling trios ascertained on high average familial LV mass indexed to height (LVMHT) using Illumina HiSeq technology. Identified missense or nonsense (MS/NS) mutations were examined for association with LVMHT using linear mixed models adjusted for age, sex, body weight, and familial relationship. To functionally assess WES findings, human induced pluripotent stem cell-derived cardiomyocytes (induced pluripotent stem cell-CM) were stimulated to induce hypertrophy; mRNA sequencing (RNA-seq) was used to determine gene expression differences associated with hypertrophy onset. Statistically significant findings under both experimental approaches identified LVH candidate genes. Candidate genes were further prioritized by seven supportive criteria that included additional association tests (two criteria), regional linkage evidence in the larger HyperGEN cohort (one criterion), and publically available gene and variant based annotations (four criteria). Results: WES reads covered 91% of the target capture region (of size 37.2 MB) with an average coverage of 65×. WES identified 31,426 MS/NS mutations among the 21 individuals. A total of 295 MS/NS variants in 265 genes were associated with LVMHT with q-value <0.25. Of the 265 WES genes, 44 were differentially expressed (P < 0.05) in hypertrophied cells. Among the 44 candidate genes identified, 5, including HLA-B, HTT, MTSS1, SLC5A12, and THBS1, met 3 of 7 supporting criteria. THBS1 encodes an adhesive glycoprotein that promotes matrix preservation in pressure-overload LVH. THBS1 gene expression was 34% higher in hypertrophied cells (P = 0.0003) and a predicted conserved and damaging NS variant in exon 13 (A2099G) was significantly associated with LVHMT (P = 4 × 10⁻⁶). Conclusion: Combining evidence from cutting-edge genetic and cellular experiments can enable identification of novel LVH risk loci.