Common Pathway Model Research Articles

Identification of shared gene signatures and biological mechanisms between preeclampsia and polycystic ovary syndrome

Preeclampsia (PE) is one of the most common complications of pregnancy and polycystic ovary syndrome (PCOS) is a prevalent metabolic and endocrinopathy disorder in women of reproductive age. Identifying the shared genetic signatures and molecular mechanisms between PCOS and PE was the objective of this study. The intersections of WGCNA module genes, PPI module genes, and PPI hub genes revealed that 8 immunity-related genes might be shared causative genes of PE and PCOS. Further, qRT-PCR results showed that TSIX/miR-223–3p/DDX58 might play a crucial role in immune dysregulation in PE and PCOS and Spearman rank correlation analysis results illustrated the potential of DDX58 as a novel diagnostic and therapeutic target for PE and PCOS. Our study demonstrated a common disease pathway model TSIX/miR-223–3p/DDX58, illustrating that immune dysregulation may be a possible mechanism of PE and PCOS, and revealed that DDX58 might be a novel predictive target for PE and PCOS.

Common genetic factors for uncontrolled eating mechanisms.

Reward-based eating drives are putative mechanisms of uncontrolled eating implicated in obesity and disordered eating (e.g., binge eating). Uncovering the genetic and environmental contributions to reward-related eating, and their genetic correlation with BMI, could shed light on key mechanisms underlying eating and weight-related disorders. We conducted a classical twin study to examine how much variance in uncontrolled eating phenotypes and body mass index (BMI) was explained by genetic factors, and the extent that these phenotypes shared common genetic factors. 353 monozygotic twins and 128 dizygotic twins completed the Reward-based Eating Drive 13 scale, which measures three distinct uncontrolled eating phenotypes (loss of control over eating, preoccupation with thoughts about food, and lack of satiety), and a demographic questionnaire which included height and weight for BMI calculation. We estimated additive genetic (A), common environmental (C), and unique environmental (E) factors for each phenotype, as well as their genetic correlations, with a multivariate ACE model. A common pathway model also estimated whether genetic variance in the uncontrolled eating phenotypes was better explained by a common latent uncontrolled eating factor. There were moderate genetic correlations between uncontrolled eating phenotypes and BMI (.26-.41). Variance from the uncontrolled eating phenotypes was also best explained by a common latent uncontrolled eating factor that was explained by additive genetic factors (52%). These results suggest that uncontrolled eating phenotypes are heritable traits that also share genetic variance with BMI. This has implications for understanding the cognitive mechanisms that underpin obesity and disordered eating. Our study clarifies the degree to which uncontrolled eating phenotypes and BMI are influenced by shared genetics and shows that vulnerability to uncontrolled eating traits is impacted by common genetic factors.

A data-driven Boolean model explains memory subsets and evolution in CD8+ T cell exhaustion

T cells play a key role in a variety of immune responses, including infection and cancer. Upon stimulation, naïve CD8+ T cells proliferate and differentiate into a variety of memory and effector cell types; however, failure to clear antigens causes prolonged stimulation of CD8+ T cells, ultimately leading to T cell exhaustion (TCE). The functional and phenotypic changes that occur during CD8+ T cell differentiation are well characterized, but the underlying gene expression state changes are not completely understood. Here, we utilize a previously published data-driven Boolean model of gene regulatory interactions shown to mediate TCE. Our network analysis and modeling reveal the final gene expression states that correspond to TCE, along with the sequence of gene expression patterns that give rise to those final states. With a model that predicts the changes in gene expression that lead to TCE, we could evaluate strategies to inhibit the exhausted state. Overall, we demonstrate that a common pathway model of CD8+ T cell gene regulatory interactions can provide insights into the transcriptional changes underlying the evolution of cell states in TCE.

Specificity in genetic and environmental risk for prescription opioid misuse and heroin use.

Many studies aggregate prescription opioid misuse (POM) and heroin use into a single phenotype, but emerging evidence suggests that their genetic and environmental influences may be partially distinct. In total, 7164 individual twins (84.12% complete pairs; 59.81% female; mean age = 30.58 years) from the Australian Twin Registry reported their lifetime misuse of prescription opioids, stimulants, and sedatives, and lifetime use of heroin, cannabis, cocaine/crack, illicit stimulants, hallucinogens, inhalants, solvents, and dissociatives via telephone interview. Independent pathway models (IPMs) and common pathway models (CPMs) partitioned the variance of drug use phenotypes into general and drug-specific genetic (a), common environmental (c), and unique environmental factors (e). An IPM with one general a and one general e factor and a one-factor CPM provided comparable fit to the data. General factors accounted for 55% (a = 14%, e = 41%) and 79% (a = 64%, e = 15%) of the respective variation in POM and heroin use in the IPM, and 25% (a = 12%, c = 8%, e = 5%) and 80% (a = 38%, c = 27%, e = 15%) of the respective variation in POM and heroin use in the CPM. Across both models, POM emerged with substantial drug-specific genetic influence (26-39% of total phenotypic variance; 69-74% of genetic variance); heroin use did not (0% of total phenotypic variance; 0% of genetic variance in both models). Prescription sedative misuse also demonstrated significant drug-specific genetic variance. Genetic variation in POM, but not heroin use, is predominantly drug-specific. Misuse of prescription medications that reduce experiences of subjective distress may be partially influenced by sources of genetic variation separate from illicit drug use.

Age-Related Variations of Genetic and Environmental Contributions to the Covariation of Fear, Distress and Externalizing Symptoms: A Twin Study in Childhood and Adolescence

The frequency with which Internalizing and Externalizing symptoms co-occur suggests that, behind both domains, there may be a common susceptibility represented by a general psychopathology factor. However, it’s still unclear whether this common susceptibility is affected by age-related variations. Internalizing (i.e., Fear and Distress) and Externalizing symptoms were evaluated in 803 twin pairs from the population-based Italian Twin Registry. Model-fitting analysis was performed separately in the 6–14 and 15–18 age groups to estimate genetic and environmental contributions to the covariance among symptoms. For the 6–14 group, a multivariate Cholesky model best fitted the data, while, for the 15–18 group, the best fit was provided by a Common Pathway model in which nearly 50% of total variance of each trait was mediated by common genetic factors. Our findings support a common susceptibility behind Internalizing and Externalizing symptoms, mainly genetic in origin, that becomes more evident at the beginning of puberty.

Phenotypic, Genetic and Environmental Architecture of the Components of Sleep Quality

The genetic and environmental underpinnings of sleep quality have been widely investigated. However, less is known about the etiology of the different sleep quality components and their associations. Subjective sleep quality has been studied most commonly using the Pittsburgh Sleep Quality Index (PSQI). Therefore, this work aimed to study the structure of sleep quality dimensions in a population-based twin sample by examining the etiology of the associations among the PSQI components themselves and between them. The sample comprised 2129 participants from the Murcia Twin Registry. In order to study the phenotypic, genetic and environmental structure of the PSQI we used three alternative multivariate twin models including all seven sub-scales of the PSQI (subjective sleep quality, latency, duration, efficiency, disturbances, use of sleeping medication and daytime dysfunction): a multivariate model (with seven separate correlated factors), a common pathway model and an independent pathway model. The multivariate correlated factors model showed the best fit to the data. All twin models indicated significant genetic overlap among most of the PSQI components, except daytime dysfunction and use of sleep medication. Bivariate heritability explained between 25 and 50% of the covariance for most associations between dimensions. Furthermore, the common pathway model showed that around one third of the variance (0.32; CI 95% 0.18.0.43) of a latent factor common to all questionnaire dimensions is explained by genetic factors. Genetic influences on a latent factor common to all questionnaire dimensions produced the same heritability estimates as the PSQI global score. However, sleep quality dimensions showed considerable specificity regarding its genetic-environmental structure.

Testing heritability of moral foundations: Common pathway models support strong heritability for the five moral foundations

Moral Foundations Theory (MFT) predicts that moral behaviour reflects at least five foundational traits, each hypothesised to be heritable. Here, we report two independent twin studies (total n = 2020), using multivariate multi-group common pathway models to test the following three predictions from the MFT: (1) The moral foundations will show significant heritability; (2) The moral foundations will each be genetically distinct and (3) The clustering of moral concerns around individualising and binding domains will show significant heritability. Supporting predictions 1 and 3, Study 1 showed evidence for significant heritability of two broad moral factors corresponding to individualising and binding domains. In Study 2, we added the second dataset, testing replication of the Study 1 model in a joint approach. This further corroborated evidence for heritable influence, showed strong influences on the individualising and binding domains (h2 = 49% and 66%, respectively) and, partially supporting prediction 2, showed foundation-specific, heritable influences on Harm/Care, Fairness/Reciprocity and Purity/Sanctity foundations. A general morality factor was required, also showing substantial genetic effects (40%). These findings indicate that moral foundations have significant genetic bases. These influenced the individual foundations themselves as well as a general concern for the individual, for the group, and overall moral concern.

Nature and nurture. Genetic and environmental factors on the relationship between back pain and sleep quality.

BackgroundChronic low back pain (LBP), neck pain (NP), and sleep quality (SQ) are genetically influenced. All three conditions frequently co‐occur and shared genetic aetiology on a pairwise base has been reported. However, to our knowledge, no study has yet investigated if these three conditions are influenced by the same genetic and environmental factors and the extent and pattern of genetic overlap between them, hence the current research.MethodsThe sample included 2134 participants. Lifetime prevalence of NP and LBP were assessed through a dichotomous self‐reported question derived from the Spanish National Health Survey. SQ was measured using the Pittsburgh Sleep Quality Index Questionnaire. A common pathway model with sleep quality and back pain as latent factors was fitted.ResultsOur results highlight that a latent back pain factor, including both NP and LBP, is explained by both genetic (41%) and environmental (59%) factors. There are also significant unique environmental factors for NP (33%) and LBP (37%) respectively. Yet, specific genetic factors were scant (9%) for NP and negligible for LBP (0%). Genetic and environmental factors affecting SQ only contribute with 3% and 5% of the variance, respectively, to the common latent back pain variable.ConclusionsNP and LBP share most of their genetic variance, while environmental effects show greater specificity for each of the back pain locations. Associations with SQ were of a limited magnitude.SignificanceOur results confirm a significant association between both chronic NP and LBP and sleep quality. Such relationship comprises both genetic and environmental factors, with a greater relative weight of the latter. A large part of the individual variance for chronic LBP and chronic NP can be accounted for by a latent common factor of ‘back pain’. Genetic influences for LBP and NP were mainly shared. However, environmental influences were common for both problems and specific for each of them in similar magnitudes.

The Etiology of Resilience to Disadvantage.

Although early-life exposure to chronic disadvantage is associated with deleterious outcomes, 40-60% of exposed youth continue to thrive. To date, little is known about the etiology of these resilient outcomes. The current study examined child twin families living in disadvantaged contexts (N=417 pairs) to elucidate the etiology of resilience. We evaluated maternal reports of the Child Behavior Checklist to examine three domains of resilience and general resilience. Genetic, shared, and nonshared environmental influences significantly contributed to social resilience (22%, 61%, 17%, respectively) and psychiatric resilience (40%, 28%, 32%, respectively), but academic resilience was influenced only by genetic and nonshared environmental influences (65% and 35%, respectively). These three domains loaded significantly onto a latent resilience factor, with factor loadings ranging from .60 to .34. A common pathway model revealed that the variance common to all three forms of resilience was predominantly explained by genetic and non-shared environmental influences (50% and 35%, respectively). These results support recent conceptualizations of resilience as a multifaceted construct influenced by both genetic and environmental influences, only some of which overlap across the various domains of resilience.

Punch-Drunk or Drunken Boxing? The Etiology of Alcohol-Related Physical Violence through Adolescence and Young Adulthood

Background Alcohol-related physical violence (ARPV) can be a causal consequence of alcohol consumption, but only for specific individuals (e.g., those predisposed to violence). Studies have not accounted for the shared etiology explaining comorbidity between alcohol use and violent behavior as a potential third-variable explanation of ARPV. The current study examined genetically-informed associations between ARPV, heavy alcohol use (HAU) and overall physical violence (OPV) in adolescence and young adulthood, by testing two proposed theories of ARPV processes (HAU causes ARPV, causal relationships depend upon OPV) and how overarching shared covariance may account for these associations. Methods Using the twin and sibling subsample from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a series of biometric models tested hypotheses individually in adolescence and young adulthood. This included estimating bivariate Cholesky and direction-of-causality models, and trivariate Cholesky, independent pathway, and common pathway models. Results HAU had a causal effect on ARPV in adolescence and young adulthood. This effect was not moderated by OPV at either developmental stage. A shared etiology or common latent factor did not explain associations between ARPV, OPV, and HAU, even though ARPV strongly covaried independently with HAU and with OPV. Finally, OPV also had a causal effect on ARPV in adolescence, and in young adulthood for adolescent-onset drinkers. Conclusions Causal theories of ARPV still hold when accounting for shared genetic and environmental variance. Further research on the exact role of violence (predispositions, environmental contexts) is required, as both phenotypes substantially (and separately) explain influences driving ARPV. Supplemental data for this article is available online at https://doi.org/10.1080/10826084.2021.1887244.

Perfectionism and Neuroticism: Evidence for a common genetic and environmental etiology

Recent meta-analyses have shown that perfectionism dimensions display significant relationships with the Big Five factors, with the strongest associations being detected between perfectionistic concerns and Neuroticism. To date, no research investigating the etiologic factors underlying these relationships has been conducted. The aim of our study was to address this literature gap by exploring the genetic and environmental influences that explain the phenotypic associations between perfectionistic concerns and Neuroticism. We used a multivariate twin design and tested two theoretical genetic models, an Independent and a Common Pathway model, on a sample of 678 Romanian twins. Univariate estimates showed that perfectionistic concerns and Neuroticism are moderately heritable (32%-46%). Multivariate analyses revealed that their phenotypic relationships were largely explained by additive genetic factors (rg between .58 and .73). The best-fit Independent Pathway model indicated that perfectionistic concerns and Neuroticism were influenced directly by some common genetic and environmental factors accounting for approximately half of their individual variance. The overlap between perfectionistic concerns and Neuroticism is mainly explained by a common genetic etiology. However, perfectionistic concerns and Neuroticism are still distinct personality features as their variances are also influenced by specific genetic and environmental factors.

The Genetic Architecture of the Clustering of Cardiometabolic Risk Factors: A Study of 8- to 17-Year-Old Chinese Twins.

We explored the genetic architecture of metabolic risk factors of cardiovascular diseases (CVDs) and their clustering in Chinese boys and girls. Seven metabolic traits (body mass index [BMI], waist circumference [WC], systolic blood pressure [SBP], diastolic blood pressure [DBP], total cholesterol [TC], triglyceride [TG], and uric acid [UA]) were measured in a sample of 1016 twins between 8 and 17 years of age, recruited from the Qingdao Twin Registry. Cholesky, independent pathway, and common pathway models were used to identify the latent genetic structure behind the clustering of these metabolic traits. Genetic architecture of these metabolic traits was largely similar in boys and girls. The highest heritability was found for BMI (a2 = 0.63) in boys and TC (a2 = .69) in girls. Three heritable factors, adiposity (BMI and WC), blood pressure (SBP and DBP), and metabolite factors (TC, TG, and UA), which formed one higher-order latent phenotype, were identified. Latent genetic, common environmental, and unique environmental factors indirectly impacted the three factors through one single latent factor. Our results suggest that there is one latent factor influencing several metabolic traits, which are known risk factors of CVDs in young Chinese twins. Latent genetic, common environmental, and unique environmental factors indirectly imposed on them. These results inform strategies for gene pleiotropic discovery and intervening of CVD risk factors during childhood and adolescence.

Heritability, stability, and prevalence of tonic and phasic irritability as indicators of disruptive mood dysregulation disorder.

Little is known about genetic and environmental influences on the components of disruptive mood dysregulation disorder (DMDD), tonic irritability (i.e., irritable mood) and phasic irritability (i.e., temper outbursts). This study examined prevalence, stability, and heritability of tonic irritability, phasic irritability, and a DMDD proxy (pDMDD) based on DSM-5 criteria. pDMDD was derived using data from clinical interviews of parents and their twins (N=1,431 twin pairs), ages 8-17, participating in Waves 1 and 2 of the Virginia Twin Study of Adolescent Behavioral Development. Biometrical modeling was used to compare a common pathway model (CPM) and an independent pathway model (IPM), and heritability estimates were obtained for pDMDD using the symptoms of irritable mood (tonic irritability; DMDD Criterion D), intense temper outbursts (phasic irritability; DMDD Criterion A), and frequent temper outbursts (phasic irritability; DMDD Criterion C). Lifetime prevalence of pDMDD was 7.46%. The stability of DMDD symptoms and the pDMDD phenotype across approximately one year were moderate (.30-.69). A CPM was a better fit to the data than an IPM. Phasic irritability loaded strongly onto the pDMDD latent factor (.89-.96) whereas tonic irritability did not (.28). Genetic influences accounted for approximately 59% of the variance in the latent pDMDD phenotype, with the remaining 41% of the variance due to unique environmental effects. The heritability of tonic irritability (54%) was slightly lower than that of frequent and intense temper (components of phasic irritability; 61% and 63%, respectively). Compared to tonic irritability, phasic irritability appears to be slightly more stable and heritable, as well as a stronger indicator of the latent factor. Furthermore, environmental experiences appear to play a substantial role in the development of irritability and DMDD, and researchers should seek to elucidate these mechanisms in future work.

Genetic and Environmental Influences on Urinary Conditions in Men: A Classical Twin Study

ObjectiveTo evaluate the genetic and environmental relationship among prostatitis and other urological conditions, including benign prostatic hyperplasia (BPH) and prostate cancer (CaP), a classical twin design and biometric modeling was used. While prostatitis—characterized by pain and voiding symptoms, no clear etiology, and functional and quality of life impairments—co-occurs with other urinary conditions, the degree of shared overlapping etiologic processes among them remains unclear. We examined the contribution of genetic and environmental factors to these conditions and the etiology of their associations at the level of genetic and environmental influences. Methods4380 monozygotic and dizygotic male twin pairs from the Vietnam Era Twin Registry reported lifetime physician-diagnosed prostatitis (combined acute and chronic), bladder problems, enlarged prostate/BPH, and CaP. Multivariate biometrical modeling estimated the magnitude of genetic and environmental influences for each condition, as well as their genetic and environmental covariance. The common pathway model tested the assumption that covariation among these urinary conditions is determined by a single latent factor. ResultsOverall prevalence of prostatitis was 2.7%. Heritability estimates ranged from 19% for bladder problems to 42% for CaP. Significant shared environmental influences were present for CaP (12%), enlarged prostate/BPH (10%) but were smaller than genetic influences. A reduced one factor common pathway model provided the best fit, suggesting that covariation among the conditions is determined by a shared latent factor. ConclusionWe identified a common, genetically-influenced factor that accounts for much of the comorbidity among these 4 disease conditions. Nonshared environmental factors also make a significant contribution.

Genes Within The Context of Development: Changes In Genetic Trait Architectures During Childhood and Adolescence

The extent to which genetic aetiologies are shared between traits and disorders naturally depends on the genetic composition of the two phenotypes. While psychiatric disorders are diagnostic entities, defined by diagnostic criteria including the age of onset, human behaviour changes continuously during development.Studying the genetic overlap between psychiatric illness and social-communication difficulties across multiple developmental stages, we identified, for example, distinct developmental profiles for childhood- versus adult-onset psychiatric disorders respectively. The genetic overlap between clinical ASD and social-communication difficulties during childhood, declined with progressing age of the trait, while the genetic overlap between clinical schizophrenia and social-communication problems was strongest for traits during later adolescence. Thus, the risk of developing these contrasting psychiatric conditions might be related to distinct sets of genes, both of which influence social communication skills, but exert their maximum influence during different periods of development. This suggests complex developmental modifications of the underlying genetic trait architecture.We have now developed a multivariate analysis framework in unrelated individuals to assess the developmental profile of genetic influences that contribute to phenotypic variation during childhood and adolescence. This analysis combines whole-genome genotyping information in unrelated individuals with structural equation modelling techniques (Genetic-relationship-matrix structural equation models, GSEM). Analogous to multivariate twin research, multivariate GSEM can include Cholesky decomposition models, common pathway models or independent pathway model, among many others. Using standard model fitting procedures, we could show that a Cholesky decomposition model, specifying two distinct genetic factors arising during childhood, fitted, for example, developmental changes in social communication abilities best. One genetic factor was common to social communication problems across development spanning 8 to 17 years (path coefficients: 0.20 to 0.54, based on standardised measures). The other factor accounted for independent phenotypic variation arising at 11 years and later ages (path coefficients: 0.20 to 0.44, based on standardised measures). Thus, genetic factors operating during mid-childhood only accounted for a limited proportion (~60%) of genetic variation at age 17 years. These incremental changes in genetic factors influencing social-communication difficulties during child and adolescent development are consistent with distinct developmental trait profiles in genetic overlap with psychiatric illness.An understanding of developmental variations in complex genetic trait architectures is therefore important for studies investigating the continuity of psychiatric disorders.

Age-Related Differences in the Structure of Genetic and Environmental Contributions to Types of Peer Victimization.

The goal of the present investigation was to clarify and compare the structure of genetic and environmental influences on different types (e.g., physical, verbal) of peer victimization experienced by youth in pre-/early adolescence and mid-/late adolescence. Physical, verbal, social, and property-related peer victimization experiences were assessed in two twin samples (306 pairs, ages 9-14 and 294 pairs, ages 15-20). Cholesky decompositions of individual differences in victimization were conducted, and independent pathway (IP) and common pathway (CP) twin models were tested in each sample. In the younger sample, a Cholesky decomposition best described the structure of genetic and environmental contributors to peer victimization, with no evidence that common additive genetic or environmental factors influence different types of peer victimization. In the older sample, common environmental factors influenced peer victimization types via a general latent liability for peer victimization (i.e., a CP model). Whereas the pre-/early adolescent sample demonstrated no evidence of a shared genetic and environmental structure for different types of peer victimization, the mid-/late adolescent sample demonstrates the emergence of an environmentally-driven latent liability for peer victimization across peer victimization types.

The stability of educational achievement across school years is largely explained by genetic factors

Little is known about the etiology of developmental change and continuity in educational achievement. Here, we study achievement from primary school to the end of compulsory education for 6000 twin pairs in the UK-representative Twins Early Development Study sample. Results showed that educational achievement is highly heritable across school years and across subjects studied at school (twin heritability ~60%; SNP heritability ~30%); achievement is highly stable (phenotypic correlations ~0.70 from ages 7 to 16). Twin analyses, applying simplex and common pathway models, showed that genetic factors accounted for most of this stability (70%), even after controlling for intelligence (60%). Shared environmental factors also contributed to the stability, while change was mostly accounted for by individual-specific environmental factors. Polygenic scores, derived from a genome-wide association analysis of adult years of education, also showed stable effects on school achievement. We conclude that the remarkable stability of achievement is largely driven genetically even after accounting for intelligence.

Developmental Changes Within the Genetic Architecture of Social Communication Behavior: A Multivariate Study of Genetic Variance in Unrelated Individuals

BackgroundRecent analyses of trait-disorder overlap suggest that psychiatric dimensions may relate to distinct sets of genes that exert maximum influence during different periods of development. This includes analyses of social communication difficulties that share, depending on their developmental stage, stronger genetic links with either autism spectrum disorder or schizophrenia. We developed a multivariate analysis framework in unrelated individuals to model directly the developmental profile of genetic influences contributing to complex traits, such as social communication difficulties, during an approximately 10-year period spanning childhood and adolescence. MethodsLongitudinally assessed quantitative social communication problems (N ≤ 5551) were studied in participants from a United Kingdom birth cohort (Avon Longitudinal Study of Parents and Children; age range, 8–17 years). Using standardized measures, genetic architectures were investigated with novel multivariate genetic-relationship-matrix structural equation models incorporating whole-genome genotyping information. Analogous to twin research, genetic-relationship-matrix structural equation models included Cholesky decomposition, common pathway, and independent pathway models. ResultsA two-factor Cholesky decomposition model described the data best. One genetic factor was common to Social Communication Disorder Checklist measures across development; the other accounted for independent variation at 11 years and later, consistent with distinct developmental profiles in trait-disorder overlap. Importantly, genetic factors operating at 8 years explained only approximately 50% of genetic variation at 17 years. ConclusionsUsing latent factor models, we identified developmental changes in the genetic architecture of social communication difficulties that enhance the understanding of autism spectrum disorder– and schizophrenia-related dimensions. More generally, genetic-relationship-matrix structural equation models present a framework for modeling shared genetic etiologies between phenotypes and can provide prior information with respect to patterns and continuity of trait-disorder overlap.

Assessing genetic and environmental influences on epicardial and abdominal adipose tissue quantities: a classical twin study.

Various adipose tissue compartments play an important role in the development of cardiometabolic diseases. The quantity of different fat compartments is influenced by genetic and environmental factors. The aim of our study was to evaluate the magnitude of genetic and environmental effects on epicardial, subcutaneous and visceral adipose tissue (EAT, SAT and VAT) quantities in a cohort of adult twin pairs. In this cross-sectional study we investigated adult twins (57 monozygotic (MZ) and 33 dizygotic (DZ) same-gender twin pairs; 180 twin subjects). We measured EAT volume using electrocardiogram-gated native computed tomography (CT) scan of the heart, and abdominal SAT and VAT areas were quantified between the third and fourth lumbar vertebra on native CT images. We calculated genetic and environmental impact on the size of various adipose tissue compartments by analyzing co-twin correlations in MZ and DZ pairs separately, and furthermore by using genetic structural equation models. In co-twin analysis, MZ twins had stronger correlations than DZ twins for EAT (rMZ=0.81, rDZ=0.32), similar to SAT and VAT quantities (rMZ=0.80, rDZ=0.68 and rMZ=0.79, rDZ=0.48, respectively). In multi-trait model fitting analysis, the overall contribution of genetic factors to EAT, SAT and VAT volumes were 80%, 78% and 70%, whereas environmental factors were 20%, 22% and 30%, respectively. Common pathway model analyses indicated that none of the EAT, SAT and VAT phenotypes was independent of the other two. Genetic factors have substantial influence, while environmental factors have only a modest impact on EAT volume, abdominal SAT and VAT quantities. There is a considerable amount of common genetic background influencing the quantities of all three adipose tissue compartments.

Discovery of cancer common and specific driver gene sets.

Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found.