Statistical Genetic Approaches to Investigate Genotype-by-Environment Interaction: Review and Novel Extension of Models.

Statistical genetic models of genotype-by-environment (G×E) interaction can be divided into two general classes, one on G×E interaction in response to dichotomous environments (e.g., sex, disease-affection status, or presence/absence of an exposure) and the other in response to continuous environments (e.g., physical activity, nutritional measurements, or continuous socioeconomic measures). Here we develop a novel model to jointly account for dichotomous and continuous environments. We develop the model in terms of a joint genotype-by-sex (for the dichotomous environment) and genotype-by-social determinants of health (SDoH; for the continuous environment). Using this model, we show how a depression variable, as measured by the Beck Depression Inventory-II survey instrument, is not only underlain by genetic effects (as has been reported elsewhere) but is also significantly determined by joint G×Sex and G×SDoH interaction effects. This model has numerous applications leading to potentially transformative research on the genetic and environmental determinants underlying complex diseases.

Metabolic syndrome traits exhibit genotype-by-environment interaction in relation to socioeconomic status in the Mexican American family heart study.

Background: Socioeconomic Status (SES) is a potent environmental determinant of health. To our knowledge, no assessment of genotype-environment interaction has been conducted to consider the joint effects of socioeconomic status and genetics on risk for metabolic disease. We analyzed data from the Mexican American Family Studies (MAFS) to evaluate the hypothesis that genotype-by-environment interaction (GxE) is an essential determinant of variation in risk factors for metabolic syndrome (MS). Methods: We employed a maximum likelihood estimation of the decomposition of variance components to detect GxE interaction. After excluding individuals with diabetes and individuals on medication for diabetes, hypertension, or dyslipidemia, we analyzed 12 MS risk factors: fasting glucose (FG), fasting insulin (FI), 2-h glucose (2G), 2-h insulin (2I), body mass index (BMI), waist circumference (WC), leptin (LP), high-density lipoprotein-cholesterol (HDL-C), triglycerides (TG), total serum cholesterol (TSC), systolic blood pressure (SBP), and diastolic blood pressure (DBP). Our SES variable used a combined score of Duncan's socioeconomic index and education years. Heterogeneity in the additive genetic variance across the SES continuum and a departure from unity in the genetic correlation coefficient were taken as evidence of GxE interaction. Hypothesis tests were conducted using standard likelihood ratio tests. Results: We found evidence of GxE for fasting glucose, 2-h glucose, 2-h insulin, BMI, and triglycerides. The genetic effects underlying the insulin/glucose metabolism component of MS are upregulated at the lower end of the SES spectrum. We also determined that the household variance for systolic blood pressure decreased with increasing SES. Conclusion: These results show a significant change in the GxE interaction underlying the major components of MS in response to changes in socioeconomic status. Further mRNA sequencing studies will identify genes and canonical gene pathways to support our molecular-level hypotheses.

Frailty index in the Colonias of the Rio Grande Valley: health related quality of life and resilience.

Background: Frailty is characterized by an accumulation of deficits that lead to vulnerability to adverse health outcomes. The Frailty Index (FI) quantifies frailty by measuring deficits that increase susceptibility to stressors. This study focused on a population of Mexican Americans living in vulnerable communities in the Rio Grande Valley of south Texas. We used a Frailty Index developed based on common health-related data--the Patient Health Questionnaire (PHQ-9) and a Health-related Quality of Life survey (Duke Health Profile). Quality of life, resilience, and frailty are interrelated and influenced by chronic illness, mental illness, poverty, cognitive impairment, and community support. Methods: We used Logistic regression analysis, factor component analysis, receiver operating characteristic curves, and odds ratios to identify potential associations between clinical variables and candidate predictor variables and seven physiological health variables, and two survey instruments. We analyzed data obtained from participants (894) that live in two Colonias located on the Texas-Mexico border. We calculated the FI with seven physiological variables, PHQ-9 score, and the 11 domain-specific Duke Profile scores, for a total of 19 health deficits. We then dichotomized FI (>0.25) and determined ROC curves through model selection to determine best predictors of frailty. Results: Females (n = 622) had a higher starting frailty, and males (n = 272) had a significantly greater change rate with age. Women score higher in anxiety, depression, anxiety/depression, and pain. The frailty index and quality of life markers are strongly inversely related; poorer quality of life leads to greater frailty independent physiological health variables, the PHQ 9, sex, and age. Conclusion: The study highlights the importance of addressing modifiable mental health and social stressors to reduce frailty. Furthermore, it suggests that factors supporting resilience and well-being, such as physical and mental health, social support, and perceived health, play a crucial role in frailty development. The findings have implications for interventions targeting vulnerable populations and emphasize the need for further research on the relationship between health-related quality of life and frailty.

Genotype-by-socioeconomic status interaction influences heart disease risk scores and carotid artery thickness in Mexican Americans: the predominant role of education in comparison to household income and socioeconomic index.

Background: Socioeconomic status (SES) is a potent environmental determinant of health. To our knowledge, no assessment of genotype-environment interaction has been conducted to consider the joint effects of socioeconomic status and genetics on risk for cardiovascular disease (CVD). We analyzed Mexican American Family Studies (MAFS) data to evaluate the hypothesis that genotype-by-environment interaction (GxE) is an important determinant of variation in CVD risk factors. Methods: We employed a linear mixed model to investigate GxE in Mexican American extended families. We studied two proxies for CVD [Pooled Cohort Equation Risk Scores/Framingham Risk Scores (FRS/PCRS) and carotid artery intima-media thickness (CA-IMT)] in relation to socioeconomic status as determined by Duncan's Socioeconomic Index (SEI), years of education, and household income. Results: We calculated heritability for FRS/PCRS and carotid artery intima-media thickness. There was evidence of GxE due to additive genetic variance heterogeneity and genetic correlation for FRS, PCRS, and CA-IMT measures for education (environment) but not for household income or SEI. Conclusion: The genetic effects underlying CVD are dynamically modulated at the lower end of the SES spectrum. There is a significant change in the genetic architecture underlying the major components of CVD in response to changes in education.

Gene-by-Environment Interaction in Non-Alcoholic Fatty Liver Disease and Depression: The Role of Hepatic Transaminases.

Non-alcoholic fatty liver disease (NAFLD) encompasses a range of liver conditions, from benign fatty accumulation to severe fibrosis. The global prevalence of NAFLD has risen to 25-30%, with variations across ethnic groups. NAFLD may advance to hepatocellular carcinoma, increases cardiovascular risk, is associated with chronic kidney disease, and is an independent metabolic disease risk factor. Assessment methods for liver health include liver biopsy, magnetic resonance imaging, ultrasound, and vibration-controlled transient elastography (VCTE by FibroScan). Hepatic transaminases are cost-effective and minimally invasive liver health assessment methods options. This study focuses on the interaction between genetic factors underlying the traits (hepatic transaminases and the FibroScan results) on the one hand and the environment (depression) on the other. We examined 525 individuals at risk for metabolic disorders. We utilized variance components models and likelihood-based statistical inference to examine potential GxE interactions in markers of NAFLD, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), and the AST/ALT ratio, and Vibration-Controlled Transient Elastography (VCTE by FibroScan). We calculated the Fibroscan-AST (FAST) score (a score that identifies the risk of progressive non-alcoholic steatohepatitis (NASH) and screened for depression using the Beck Depression Inventory-II (BDI-II). We identified significant G × E interactions for AST/ALT ratio × BDI-II, but not AST, ALT, or the FAST score. Our findings support that genetic factors play a role in hepatic transaminases, especially the AST/ALT ratio, with depression influencing this relationship. These insights contribute to understanding the complex interplay of genetics, environment, and liver health, potentially guiding future personalized interventions.

Non-alcoholic Fatty Liver Disease and Depression: Evidence for Genotype × Environment Interaction in Mexican Americans.

This study examines the impact of G × E interaction effects on non-alcoholic fatty liver disease (NAFLD) among Mexican Americans in the Rio Grande Valley (RGV) of South Texas. We examined potential G × E interaction using variance components models and likelihood-based statistical inference in the phenotypic expression of NAFLD, including hepatic steatosis and hepatic fibrosis (identified using vibration controlled transient elastography and controlled attenuation parameter measured by the FibroScan Device). We screened for depression using the Beck Depression Inventory-II (BDI-II). We identified significant G × E interactions for hepatic fibrosis × BDI-II. These findings provide evidence that genetic factors interact with depression to influence the expression of hepatic fibrosis.

Influence of the Human Lipidome on Epicardial Fat Volume in Mexican American Individuals.

Introduction: Cardiovascular disease (CVD) is the leading cause of mortality worldwide and is the leading cause of death in the US. Lipid dysregulation is a well-known precursor to metabolic diseases, including CVD. There is a growing body of literature that suggests MRI-derived epicardial fat volume, or epicardial adipose tissue (EAT) volume, is linked to the development of coronary artery disease. Interestingly, epicardial fat is also actively involved in lipid and energy homeostasis, with epicardial adipose tissue having a greater capacity for release and uptake of free fatty acids. However, there is a scarcity of knowledge on the influence of plasma lipids on EAT volume. Aim: The focus of this study is on the identification of novel lipidomic species associated with CMRI-derived measures of epicardial fat in Mexican American individuals. Methods: We performed lipidomic profiling on 200 Mexican American individuals. High-throughput mass spectrometry enabled rapid capture of precise lipidomic profiles, providing measures of 799 unique species from circulating plasma samples. Because of our extended pedigree design, we utilized a standard quantitative genetic linear mixed model analysis to determine whether lipids were correlated with EAT by formally testing for association between each lipid species and the CMRI epicardial fat phenotype. Results: After correction for multiple testing using the FDR approach, we identified 135 lipid species showing significant association with epicardial fat. Of those, 131 lipid species were positively correlated with EAT, where increased circulating lipid levels were correlated with increased epicardial fat. Interestingly, the top 10 lipid species associated with an increased epicardial fat volume were from the deoxyceramide (Cer(m)) and triacylglycerol (TG) families. Deoxyceramides are atypical and neurotoxic sphingolipids. Triacylglycerols are an abundant lipid class and comprise the bulk of storage fat in tissues. Pathologically elevated TG and Cer(m) levels are related to CVD risk and, in our study, to EAT volume. Conclusion: Our results indicate that specific lipid abnormalities such as enriched saturated triacylglycerols and the presence of toxic ceramides Cer(m) in plasma of our individuals could precede CVD with increased EAT volume.

Frailty Index in the Colonias on the US-Mexico Border: A Special Report.

Frailty is the age-related decline in well-being. The Frailty index (FI) measures the accumulation of health deficits and reflects biopsychosocial and cultural determinants of well-being. Frailty is measured as a static phenotype or as a Frailty Index comprising a ratio of suffered health deficits and total deficits. We report a Frailty Index calculated from routinely measured clinical variables gathered from residents of two Colonias (neighborhoods) in South Texas. A Colonia is a predominantly Hispanic, economically distressed, unincorporated neighborhood. We analyzed retrospective data from 894 patients that live in two Colonias located on the Texas-Mexico border. We calculated the FI with seven physiological variables, PHQ-9 score, and the 11 domain-specific Duke Profile scores, for a total of 19 possible health deficits. FI against age separately in males (n = 272) and females (n = 622) was regressed. Females had a significantly higher starting frailty, and males had a significantly greater change rate with age. FI against age for Cameron Park Colonia and Indian Hills Colonia was regressed. We calculated a significantly higher starting FI in Indian Hills and a significantly greater change rate in Cameron Park residents. Frailty's contributors are complex, especially in neighborhoods of poverty, immigration, low education level, and high prevalence of chronic disease. We report baseline Frailty Index data from two Colonias in South Texas and the clinical and research implications.

Quantitative HLA-class-II/factor VIII (FVIII) peptidomic variation in dendritic cells correlates with the immunogenic potential of therapeutic FVIII proteins in hemophilia A.

BACKGROUND: Plasma-derived (pd) or recombinant (r) therapeutic factor VIII proteins (FVIIIs) are infused to arrest/prevent bleeding in patients with hemophilia A (PWHA). However, FVIIIs are neutralized if anti-FVIII-antibodies (inhibitors) develop. Accumulating evidence suggests that pdFVIIIs with von Willebrand factor (VWF) are less immunogenic than rFVIIIs and that distinct rFVIIIs are differentially immunogenic. Since inhibitor development is T-helper-cell-dependent, human leukocyte antigen (HLA)-class-II (HLAcII) molecules constitute an important early determinant. OBJECTIVES: Use dendritic cell (DC)-protein processing/presentation assays with mass-spectrometric and peptide-proteomic analyses to quantify the DP-bound, DQ-bound, and DR-bound FVIII-derived peptides in individual HLAcII repertoires and compare the immunogenic potential of six distinct FVIIIs based on their measured peptide counts. PATIENTS/METHODS: Monocyte-derived DCs from normal donors and/or PWHA were cultured with either: Mix-rFVIII, a VWF-free equimolar mixture of a full-length (FL)-rFVIII [Advate® (Takeda)] and four distinct B-domain-deleted (BDD)-rFVIIIs [Xyntha® (Pfizer), NovoEight® (Novo-Nordisk), Nuwiq® (Octapharma), and Afstyla® (CSL Behring GmBH)]; a pdFVIII + pdVWF [Beriate® (CSL Behring GmBH)]; Advate ± pdVWF; Afstyla ± pdVWF; and Xyntha + pdVWF. RESULTS: We showed that (i) Beriate had a significantly lower immunogenic potential than Advate ± pdVWF, Afstyla - pdVWF, and Mix-rFVIII; (ii) distinct FVIIIs differed significantly in their immunogenic potential in that, in addition to (i), Afstyla + pdVWF had a significantly lower immunogenic potential than Beriate, while the immunogenic potential of Beriate was not significantly different from that of Xyntha + pdVWF; and (iii) rFVIIIs with pdVWF had significantly lower immunogenic potentials than the same rFVIIIs without pdVWF. CONCLUSIONS: Our results provide HLAcII peptidomic level explanations for several important clinical observations/issues including the differential immunogenicity of distinct FVIIIs and the role of HLAcII genetics in inhibitor development.

Estimating the Heritability of Experiencing Child Maltreatment in an Extended Family Design.

Child-driven genetic factors can contribute to negative parenting and may increase the risk of being maltreated. Experiencing childhood maltreatment may be partly heritable, but results of twin studies are mixed. In the current study, we used a cross-sectional extended family design to estimate genetic and environmental effects on experiencing child maltreatment. The sample consisted of 395 individuals (225 women; Mage = 38.85 years, rangeage = 7-88 years) from 63 families with two or three participating generations. Participants were oversampled for experienced maltreatment. Self-reported experienced child maltreatment was measured using a questionnaire assessing physical and emotional abuse, and physical and emotional neglect. All maltreatment phenotypes were partly heritable with percentages for h2 ranging from 30% (SE = 13%) for neglect to 62% (SE = 19%) for severe physical abuse. Common environmental effects (c2) explained a statistically significant proportion of variance for all phenotypes except for the experience of severe physical abuse (c2 = 9%, SE = 13%, p = .26). The genetic correlation between abuse and neglect was ρg = .73 (p = .02). Common environmental variance increased as socioeconomic status (SES) decreased (p = .05), but additive genetic and unique environmental variances were constant across different levels of SES.

UniMóvil: A Mobile Health Clinic Providing Primary Care to the Colonias of the Rio Grande Valley, South Texas.

Background: We describe a mobile unit (UniMóvil) designed to improve poor healthcare access delivery to residents in two South Texas underserved Colonias. The interprofessional team measured seven clinical outcomes [obesity, diabetes, hypertension, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C) levels, and depression], and using the Duke Health Profile, assessed the health-related quality of life (HrQoL). Methods: The investigators used previously reported disease prevalence, an implementation model, and community needs-assessments to design an outreach healthcare delivery model. A retrospective review of the cohort provides data used to determine potential predictors of clinical variables, 11 domains of HrQOL, and inter/intra Colonia differences. Results: The average age of patients was 45 years-old and females represented 67% of the population served. Results include a high prevalence of obesity (55.5%), hypertension (39%), diabetes (32.5%), and depression (19%), gender differences, and inter-Colonia differences. A generalized linear mixed model analysis provided associations between clinical outcomes and predictors (age, sex, BMI, PHQ-9 score, HbA1c, blood pressure, serum cholesterol, low HDL, triglycerides, and HrQOL domains). The HrQol domain of low self-perceived health, relates to obesity, diabetes, low HDL, and depression. Depression predicted all 11 domains of the HrQol. Conclusion: The prevalence of diabetes, hypertension, obesity, and depression remains epidemic. Mobile clinics increase access and address highly prevalent illnesses in the Colonias. The data collected can be used to address chronic disease and quality of life, focus care, and direct research in high-need underserved areas.

Peptides identified on monocyte-derived dendritic cells: a marker for clinical immunogenicity to FVIII products.

The immunogenicity of protein therapeutics is an important safety and efficacy concern during drug development and regulation. Strategies to identify individuals and subpopulations at risk for an undesirable immune response represent an important unmet need. The major histocompatibility complex (MHC)-associated peptide proteomics (MAPPs) assay directly identifies the presence of peptides derived from a specific protein therapeutic on a donor's MHC class II (MHC-II) proteins. We applied this technique to address several questions related to the use of factor VIII (FVIII) replacement therapy in the treatment of hemophilia A (HA). Although >12 FVIII therapeutics are marketed, most fall into 3 categories: (i) human plasma-derived FVIII (pdFVIII), (ii) full-length (FL)-recombinant FVIII (rFVIII; FL-rFVIII), and (iii) B-domain-deleted rFVIII. Here, we investigated whether there are differences between the FVIII peptides found on the MHC-II proteins of the same individual when incubated with these 3 classes. Based on several observational studies and a prospective, randomized, clinical trial showing that the originally approved rFVIII products may be more immunogenic than the pdFVIII products containing von Willebrand factor (VWF) in molar excess, it has been hypothesized that the pdFVIII molecules yield/present fewer peptides (ie, potential T-cell epitopes). We have experimentally tested this hypothesis and found that dendritic cells from HA patients and healthy donors present fewer FVIII peptides when administered pdFVIII vs FL-rFVIII, despite both containing the same molar VWF excess. Our results support the hypothesis that synthesis of pdFVIII under physiological conditions could result in reduced heterogeneity and/or subtle differences in structure/conformation which, in turn, may result in reduced FVIII proteolytic processing relative to FL-rFVIII.

The genetic and environmental etiology of child maltreatment in a parent-based extended family design.

Child maltreatment has been associated with various cumulative risk factors. However, little is known about the extent to which genetic and environmental factors contribute to individual differences between parents in perpetrating child maltreatment. To estimate the relative contribution of genetic and environmental factors to perpetrating maltreatment we used a parent-based extended family design. Child-reported perpetrated maltreatment was available for 556 parents (283 women) from 63 families. To explore reporter effects (i.e., child perspective on maltreatment), child reports were compared to multi-informant reports. Based on polygenic model analyses, most of the variance related to the perpetration of physical abuse and emotional neglect was explained by common environmental factors (physical abuse: c2 = 59%, SE = 12%, p = .006; emotional neglect: c2 = 47%, SE = 8%, p < .001) whereas genetic factors did not significantly contribute to the model. For perpetrated emotional abuse, in contrast, genetic factors did significantly contribute to perpetrated emotional abuse (h2 = 33%, SE = 8%, p < .001), whereas common environment factors did not. Multi-informant reports led to similar estimates of genetic and common environmental effects on all measures except for emotional abuse, where a multi-informant approach yielded higher estimates of the common environmental effects. Overall, estimates of unique environment, including measurement error, were lower using multi-informant reports. In conclusion, our findings suggest that genetic pathways play a significant role in perpetrating emotional abuse, while physical abuse and emotional neglect are transmitted primarily through common environmental factors. These findings imply that interventions may need to target different mechanisms dependings on maltreatment type.

Genetic and environmental (physical fitness and sedentary activity) interaction effects on cardiometabolic risk factors in Mexican American children and adolescents.

Knowledge on genetic and environmental (G × E) interaction effects on cardiometabolic risk factors (CMRFs) in children is limited.  The purpose of this study was to examine the impact of G × E interaction effects on CMRFs in Mexican American (MA) children (n = 617, ages 6-17 years). The environments examined were sedentary activity (SA), assessed by recalls from "yesterday" (SAy) and "usually" (SAu) and physical fitness (PF) assessed by Harvard PF scores (HPFS). CMRF data included body mass index (BMI), waist circumference (WC), fat mass (FM), fasting insulin (FI), homeostasis model of assessment-insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), systolic (SBP) and diastolic (DBP) blood pressure, and number of metabolic syndrome components (MSC). We examined potential G × E interaction in the phenotypic expression of CMRFs using variance component models and likelihood-based statistical inference. Significant G × SA interactions were identified for six CMRFs: BMI, WC, FI, HOMA-IR, MSC, and HDL, and significant G × HPFS interactions were observed for four CMRFs: BMI, WC, FM, and HOMA-IR. However, after correcting for multiple hypothesis testing, only WC × SAy, FM × SAy, and FI × SAu interactions became marginally significant. After correcting for multiple testing, most of CMRFs exhibited significant G × E interactions (Reduced G × E model vs. Constrained model). These findings provide evidence that genetic factors interact with SA and PF to influence variation in CMRFs, and underscore the need for better understanding of these relationships to develop strategies and interventions to effectively reduce or prevent cardiometabolic risk in children.

Sex-specific genetic effects in physical activity: results from a quantitative genetic analysis.

BACKGROUND: The objective of this study is to present a model to estimate sex-specific genetic effects on physical activity (PA) levels and sedentary behaviour (SB) using three generation families. METHODS: The sample consisted of 100 families covering three generations from Portugal. PA and SB were assessed via the International Physical Activity Questionnaire short form (IPAQ-SF). Sex-specific effects were assessed by genotype-by-sex interaction (GSI) models and sex-specific heritabilities. GSI effects and heterogeneity were tested in the residual environmental variance. SPSS 17 and SOLAR v. 4.1 were used in all computations. RESULTS: The genetic component for PA and SB domains varied from low to moderate (11% to 46%), when analyzing both genders combined. We found GSI effects for vigorous PA (p = 0.02) and time spent watching television (WT) (p < 0.001) that showed significantly higher additive genetic variance estimates in males. The heterogeneity in the residual environmental variance was significant for moderate PA (p = 0.02), vigorous PA (p = 0.006) and total PA (p = 0.001). Sex-specific heritability estimates were significantly higher in males only for WT, with a male-to-female difference in heritability of 42.5 (95% confidence interval: 6.4, 70.4). CONCLUSIONS: Low to moderate genetic effects on PA and SB traits were found. Results from the GSI model show that there are sex-specific effects in two phenotypes, VPA and WT with a stronger genetic influence in males.

Evaluation of estimated genetic values and their application to genome-wide investigation of systolic blood pressure.

The concept of breeding values, an individual's phenotypic deviation from the population mean as a result of the sum of the average effects of the genes they carry, is of great importance in livestock, aquaculture, and cash crop industries where emphasis is placed on an individual's potential to pass desirable phenotypes on to the next generation. As breeding or genetic values (as referred to here) cannot be measured directly, estimated genetic values (EGVs) are based on an individual's own phenotype, phenotype information from relatives, and, increasingly, genetic data. Because EGVs represent additive genetic variation, calculating EGVs in an extended human pedigree is expected to provide a more refined phenotype for genetic analyses. To test the utility of EGVs in genome-wide association, EGVs were calculated for 847 members of 20 extended Mexican American families based on 100 replicates of simulated systolic blood pressure. Calculations were performed in GAUSS to solve a variation on the standard Best Linear Unbiased Predictor (BLUP) mixed model equation with age, sex, and the first 3 principal components of sample-wide genetic variability as fixed effects and the EGV as a random effect distributed around the relationship matrix. Three methods of calculating kinship were considered: expected kinship from pedigree relationships, empirical kinship from common variants, and empirical kinship from both rare and common variants. Genome-wide association analysis was conducted on simulated phenotypes and EGVs using the additive measured genotype approach in the SOLAR software package. The EGV-based approach showed only minimal improvement in power to detect causative loci.

Genotype by sex and genotype by age interactions with sedentary behavior: the Portuguese Healthy Family Study.

Sedentary behavior (SB) expression and its underlying causal factors have been progressively studied, as it is a major determinant of decreased health quality. In the present study we applied Genotype x Age (GxAge) and Genotype x Sex (GxSex) interaction methods to determine if the phenotypic expression of different SB traits is influenced by an interaction between genetic architecture and both age and sex. A total of 1345 subjects, comprising 249 fathers, 327 mothers, 334 sons and 325 daughters, from 339 families of The Portuguese Healthy Family Study were included in the analysis. SB traits were assessed by means of a 3-d physical activity recall, the Baecke and IPAQ questionnaires. GxAge and GxSex interactions were analyzed using SOLAR 4.0 software. Sedentary behaviour heritability estimates were not always statistically significant (p>0.05) and ranged from 3% to 27%. The GxSex and GxAge interaction models were significantly better than the single polygenic models for TV (min/day), EEsed (kcal/day), personal computer (PC) usage and physical activty (PA) tertiles. The GxAge model is also significantly better than the polygenic model for Sed (min/day). For EEsed, PA tertiles, PC and Sed, the GxAge interaction was significant because the genetic correlation between SB environments was significantly different from 1. Further, PC and Sed variance heterogeneity among distinct ages were observed. The GxSex interaction was significant for EEsed due to genetic variance heterogeneity between genders and for PC due to a genetic correlation less than 1 across both sexes. Our results suggest that SB expression may be influenced by the interactions between genotype with both sex and age. Further, different sedentary behaviors seem to have distinct genetic architectures and are differentially affected by age and sex.

Genetic prediction in the Genetic Analysis Workshop 18 sequencing data.

High-throughput sequencing data can be used to predict phenotypes from genotypes, and this corresponds to establishing a prognostic model. In extended pedigrees the relatedness of subjects provides additional information so that genetic values, fixed or random genetic components, and heritability can be estimated. At the Genetic Analysis Workshop 18, the working group on genetic prediction dealt with both establishing a prognostic model and, in one contribution, comparing standard logistic regression with robust logistic regression in a sample of unrelated affected or unaffected individuals. Results of both logistic regression approaches were similar. All other contributions to this group used extended family data, in general using the quantitative trait blood pressure. The individual contributions varied in several important aspects, such as the estimation of the kinship matrix and the estimation method. Contributors chose various approaches for model validation, including different versions of cross-validation or within-family validation. Within-family validation included model building in the upper generations and validation in later generations. The choice of the statistical model and the computational algorithm had substantial effects on computation time. If decorrelation approaches were applied, the computational burden was substantially reduced. Some software packages estimated negative eigenvalues, although eigenvalues of correlation matrices should be non-negative. Most statistical models and software packages have been developed for experimental crosses and planned breeding programs. With their specialized pedigree structures, they are not sufficiently flexible to accommodate the variability of human pedigrees in general, and improved implementations are required.

Plasma levels of soluble interleukin 1 receptor accessory protein are reduced in obesity.

CONTEXT: Adipokines actuate chronic, low-grade inflammation through a complex network of immune markers, but the current understanding of these networks is incomplete. The soluble isoform of the IL-1 receptor accessory protein (sIL1RAP) occupies an important position in the inflammatory pathways involved in obesity. The pathogenetic and clinical influences of sIL1RAP are unknown. OBJECTIVE: The objective of the study was to elucidate whether plasma levels of sIL1RAP are reduced in obesity, using affluent clinical, biochemical, and genetic data from two diverse cohorts. DESIGN, SETTING, AND PARTICIPANTS: The study was conducted in two cohorts: the San Antonio Family Heart Study (n = 1397 individuals from 42 families) and South Asians living in Mauritius, n = 230). MAIN OUTCOME MEASURES: Plasma sIL1RAP levels were measured using an ELISA. The genetic basis of sIL1RAP levels were investigated using both a large-scale gene expression profiling study and a genome-wide association study. RESULTS: A significant decrease in plasma sIL1RAP levels were observed in obese subjects, even after adjustment for age and sex. The sIL1RAP levels demonstrated a strong inverse association with obesity measures in both populations. All associations were more significant in females. Plasma sIL1RAP levels were significantly heritable, correlated with IL1RAP transcript levels (NM_134470), showed evidence for shared genetic influences with obesity measures and were significantly associated with the rs2885373 single-nucleotide polymorphism (P = 6.7 × 10(-23)) within the IL1RAP gene. CONCLUSIONS: Plasma sIL1RAP levels are reduced in obesity and can potentially act as biomarkers of obesity. Mechanistic studies are required to understand the exact contribution of sIL1RAP to the pathogenesis of obesity.

Gene-by-age effects on BMI from birth to adulthood: the Fels Longitudinal Study.

OBJECTIVES: Genome wide association studies have shown 32 loci to influence BMI in European-American adults but replication in other studies is inconsistent and may be attributed to gene-by-age effects. The aims of this study were to determine if the influence of the summed risk score of these 32 loci (GRS) on BMI differed across age from birth to 40 years, and to determine if additive genetic effects other than those in the GRS differed by age. METHODS: Serial measures of BMI were calculated at 0, 1, 3, 6, 9, 12, 18, and 28 months, and 4, 7, 11, 15, 19, 23, 30, and 40 years for 1,176 (605 females, 571 males) European-American participants in the Fels Longitudinal Study. SOLAR was used for genetic analyses. RESULTS: GRS was significant (P < 0.05) at ages: 6, 9 months, 4-15 years, and 23-40 years. Remaining additive genetic effects independently influenced BMI (P < 5.3 × 10(-5) , 0.40 < h(2) < 0.76). Some genetic correlations between ages were not significant. Differential GRS effects did not retain significance after multiple comparisons adjustments. CONCLUSIONS: While well-known BMI variants do not appear to have significant differential effects, other additive genes differ over the lifespan.