A common genetic variant is associated with adult and childhood obesity

Development of genome-wide association studies on childhood obesity and its indicators: A scoping review and enrichment analysis

BACKGROUND

The progress of genome-wide association studies (GWAS) in childhood obesity and its indicators is challenging and there are differences in genetic studies in children and adults.

OBJECTIVE

To illustrate the history of the development of GWAS in childhood obesity and its indicators and summarize the GWAS loci.

METHODS

PubMed, Web of Science, Embase and GWAS Catalog databases were systematically searched from 1 January 2005 to 19 October 2022 for literature related to GWAS of childhood BMI, body fatness and obesity. The nearest genes were used as positional genes to perform gene set analyses including the enrichment of pathways, tissues and diseases.

RESULTS

Twenty articles published between 2007 and 2021 were included in this scoping review, which identified 116 SNPs reaching genome-wide significance with childhood BMI (n = 50), body fatness (n = 31) and obesity (n = 35). The study populations were European in 16 studies, non-European in three studies (1 East Asian; 1 American; 1 Mexican) and trans-ancestry in one study. Several enriched pathways, tissues and diseases were identified through enrichment analysis of genes associated with childhood obesity and its indicators.

CONCLUSIONS

The innovations in tools and methods enable GWAS to better explore the genetic characteristics of obesity in children and adolescents. However, the number of GWAS in American, Asian and African populations is limited compared to the European population.

Genetics and Epigenetics in Obesity: What Do We Know so Far?

PURPOSE OF REVIEW

Enormous progress has been made in understanding the genetic architecture of obesity and the correlation of epigenetic marks with obesity and related traits. This review highlights current research and its challenges in genetics and epigenetics of obesity.

RECENT FINDINGS

Recent progress in genetics of polygenic traits, particularly represented by genome-wide association studies, led to the discovery of hundreds of genetic variants associated with obesity, which allows constructing polygenic risk scores (PGS). In addition, epigenome-wide association studies helped identifying novel targets and methylation sites being important in the pathophysiology of obesity and which are essential for the generation of methylation risk scores (MRS). Despite their great potential for predicting the individual risk for obesity, the use of PGS and MRS remains challenging. Future research will likely discover more loci being involved in obesity, which will contribute to better understanding of the complex etiology of human obesity. The ultimate goal from a clinical perspective will be generating highly robust and accurate prediction scores allowing clinicians to predict obesity as well as individual responses to body weight loss-specific life-style interventions.

Genetics: A Starting Point for the Prevention and the Treatment of Obesity

Obesity is a common, serious, and costly disease. More than 1 billion people worldwide are obese-650 million adults, 340 million adolescents, and 39 million children. The WHO estimates that, by 2025, approximately 167 million people-adults and children-will become less healthy because they are overweight or obese. Obesity-related conditions include heart disease, stroke, type 2 diabetes, and certain types of cancer. These are among the leading causes of preventable, premature death. The estimated annual medical cost of obesity in the United States was nearly $173 billion in 2019 dollars. Obesity is considered the result of a complex interaction between genes and the environment. Both genes and the environment change in different populations. In fact, the prevalence changes as the result of eating habits, lifestyle, and expression of genes coding for factors involved in the regulation of body weight, food intake, and satiety. Expression of these genes involves different epigenetic processes, such as DNA methylation, histone modification, or non-coding micro-RNA synthesis, as well as variations in the gene sequence, which results in functional alterations. Evolutionary and non-evolutionary (i.e., genetic drift, migration, and founder's effect) factors have shaped the genetic predisposition or protection from obesity in modern human populations. Understanding and knowing the pathogenesis of obesity will lead to prevention and treatment strategies not only for obesity, but also for other related diseases.

Explaining adult obesity, severe obesity, and BMI: Five decades of change

Obesity rates have increased across all segments of society since the late 1970s, but the reason behind population-level increases in body weight remains unclear. We used the 1971-2020 NHANES data to examine whether the observed trend in obesity prevalence is attributable to changing public health behaviors (i.e., intracohort change) or changing publics (i.e., cohort replacement). We partitioned total change in mean BMI, and rates of obesity and severe obesity, into its IC and CR components using linear and algebraic decomposition methods. We found that the IC mechanism (i.e., broad sectors of individuals changing) plays a dominant role in the overall increase in mean BMI, and obesity and severe obesity prevalence. Birth cohort membership (i.e., the CR mechanism) is also influencing mean BMI, and rates of obesity and severe obesity, but in differing ways. Specifically, the large positive IC and the small positive CR effects are amplifying one another, thus creating a steep increase in the observed rates of severe obesity. Conversely, the large positive IC effect is offset by a small negative CR effect, which created a more gradual rise in mean BMI and rates of obesity. Furthermore, we computed total change for models that entered separately sociodemographic, lifestyle, nutritional, and physical activity measures to estimate differences in mean BMI, and rates of obesity and severe obesity, among cohorts and time periods. Adjustment for all the compositional differences among the cohorts during the study period indicate that a combination of a more pronounced IC and a less pronounced CR drove the observed increase in mean BMI, and rates of obesity and severe obesity. Thus, "universal prevention" (i.e., entire community) strategies for healthy weight promotion may need to be combined with "selective prevention" (i.e., at-risk groups) and/or "targeted prevention" (i.e., at-risk individuals) approaches in order to reverse the obesity epidemic.

Gene-Nutrient Interactions in Obesity: COBLL1 Genetic Variants Interact with Dietary Fat Intake to Modulate the Incidence of Obesity

The COBLL1 gene is associated with leptin, a hormone important for appetite and weight maintenance. Dietary fat is a significant factor in obesity. This study aimed to determine the association between COBLL1 gene, dietary fat, and incidence of obesity. Data from the Korean Genome and Epidemiology Study were used, and 3055 Korean adults aged ≥ 40 years were included. Obesity was defined as a body mass index ≥ 25 kg/m². Patients with obesity at baseline were excluded. The effects of the COBLL1 rs6717858 genotypes and dietary fat on incidence of obesity were evaluated using multivariable Cox proportional hazard models. During an average follow-up period of 9.2 years, 627 obesity cases were documented. In men, the hazard ratio (HR) for obesity was higher in CT, CC carriers (minor allele carriers) in the highest tertile of dietary fat intake than for men with TT carriers in the lowest tertile of dietary fat intake (Model 1: HR: 1.66, 95% confidence interval [CI]: 1.07-2.58; Model 2: HR: 1.63, 95% CI: 1.04-2.56). In women, the HR for obesity was higher in TT carriers in the highest tertile of dietary fat intake than for women with TT carriers in the lowest tertile of dietary fat intake (Model 1: HR: 1.49, 95% CI: 1.08-2.06; Model 2: HR: 1.53, 95% CI: 1.10-2.13). COBLL1 genetic variants and dietary fat intake had different sex-dependent effects in obesity. These results imply that a low-fat diet may protect against the effects of COBLL1 genetic variants on future obesity risk.

Association of common genetic variants with body mass index in Russian population

BACKGROUND

Overweight is the scourge of modern society and a major risk factor for many diseases. For this reason, understanding the genetic component predisposing to high body mass index (BMI) seems to be an important task along with preventive measures aimed at improving eating behavior and increasing physical activity.

METHODS

We analyzed genetic data of a European cohort (n = 21,080, 47.25% women, East Slavs ancestry >80%) for 5 frequently found genes in the context of association with obesity: IPX3 (rs3751723), MC4R (rs17782313), TMEM18 (rs6548238), PPARG (rs1801282) and FTO (rs9939609).

RESULTS

Our study revealed significant associations of FTO (rs9939609) (β = 0.37 (kg/m²)/allele, p = <2 × 10^-16), MC4R (rs17782313) (β = 0.28 (kg/m²)/allele, p = 5.79 × 10^-9), TMEM18 (rs6548238) (β = 0.29 (kg/m²)/allele, p = 2.43 × 10^-8) with BMI and risk of obesity.

CONCLUSIONS

The results confirm the contribution of FTO, M4CR, and TMEM18 genes to the mechanism of body weight regulation and control.

Strategies to identify causal common genetic variants and corresponding effector genes for paediatric obesity

BACKGROUND

Childhood obesity rates are on the rise, but there are currently no effective therapies available to slow or halt their progression. Although environmental and lifestyle factors have been implicated in its pathogenesis, childhood obesity is considered a complex disorder with a clear genetic component. Intense genome-wide association study (GWAS) efforts through large-scale collaborations have enabled the discovery of genetic loci robustly associated with childhood obesity beyond the classic FTO locus. That said, GWAS itself does not pinpoint the actual underlying causal effector genes, but rather just yields association signals in the genome.

OBJECTIVE

This review aims to outline what has been elucidated thus far on the genetic aetiology of commong childhood obesity and to describe strategies to identify and validate both causal common genetic variants and their corresponding effector genes.

RESULTS

Relevant cell types for molecular studies can be identified by gene set enrichment analysis and considering known biology of obesity-related physiological processes. Putatively causal single nucleotide polymorphisms (SNPs) can be identified by several methods including statistical fine mapping and 'assay for transposase accessible chromatin sequencing' (ATAC-seq). Variant to gene mapping can then nominate effector genes likely regulated by cis-regulatory elements harbouring putatively causal SNPs. A SNP's cis-regulatory activity can be functionally validated by several in vitro methods including luciferase assay and CRISPR approaches. These CRISPR approaches can also be used to investigate how dysregulatn of effector genes may confer obesity risk.

CONCLUSION

Uncovering the causative genes related to GWAS signals and elucidating their functional contributions to paediatric obesity with these strategies will deepen our understanding of this disease and serve better treatment outcomes.

Natural Immunity against HIV-1: Progression of Understanding after Association Studies

Natural immunity against HIV has been observed in many individuals in the world. Among them, a group of female sex workers enrolled in the Pumwani sex worker cohort remained HIV uninfected for more than 30 years despite high-risk sex work. Many studies have been carried out to understand this natural immunity to HIV in the hope to develop effective vaccines and preventions. This review focuses on two such examples. These studies started from identifying immunogenetic or genetic associations with resistance to HIV acquisition, and followed up with an in-depth investigation to understand the biological relevance of the correlations of protection, and to develop and test novel vaccines and preventions.

The Importance of a Genome-Wide Association Analysis in the Study of Alternative Splicing Mutations in Plants with a Special Focus on Maize

Alternative splicing is an important mechanism for regulating gene expressions at the post-transcriptional level. In eukaryotes, the genes are transcribed in the nucleus to produce pre-mRNAs and alternative splicing can splice a pre-mRNA to eventually form multiple different mature mRNAs, greatly increasing the number of genes and protein diversity. Alternative splicing is involved in the regulation of various plant life activities, especially the response of plants to abiotic stresses and is also an important process of plant growth and development. This review aims to clarify the usefulness of a genome-wide association analysis in the study of alternatively spliced variants by summarizing the application of alternative splicing, genome-wide association analyses and genome-wide association analyses in alternative splicing, as well as summarizing the related research progress.

The Role of Modifiable, Self-Empowerment-Oriented Variables to Promote Health-Related Quality of Life Among Inadequately Insured Americans

Inadequately insured Americans experience a disproportionately low health-related quality of life (HRQoL)-a multidimensional and subjective indicator of health associated with premature mortality. Although the inadequately insured are a growing and at-risk group of individuals, little research has examined factors associated with HRQoL within this population. Health Self-Empowerment Theory (HSET) and precision prevention influenced the conceptualization of this study. HSET is a health empowerment theory that recognizes the effects of certain cognitive-behavioral variables on health promotion within at-risk groups. Precision prevention advocates for individual or precise group-specific tailored and optimized health promotion approaches based on key sociodemographic variables. We investigated the impact of HSET variables on mental and physical HRQoL among 279 inadequately insured women and men who completed a questionnaire assessing HRQoL, health self-efficacy, health motivation, and active coping. Among the women in our sample, results indicate that exercise and psychological well-being self-efficacy were significantly and positively associated with mental and physical HRQoL. Among men, psychological well-being and responsible health practices self-efficacy, in addition to active coping, were significantly and positively associated with mental HRQoL. Psychological well-being self-efficacy and active coping were significantly and positively associated with physical HRQoL among men. The findings of our study suggest that HSET variables play an important role in the development of tailored HRQoL-promotion interventions for inadequately insured Americans, and that the roles of those variables may differ based on gender.

Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy

Rapid methodological advances in statistical and computational genomics have enabled researchers to better identify and interpret both rare and common variants responsible for complex human diseases. As we continue to see an expansion of these advances in the field, it is now imperative for researchers to understand the resources and methodologies available for various data types and study designs. In this review, we provide an overview of recent methods for identifying rare and common variants and understanding their roles in disease etiology. Additionally, we discuss the strategy, challenge, and promise of gene therapy. As computational and statistical approaches continue to improve, we will have an opportunity to translate human genetic findings into personalized health care.

Novel recessive locus for body mass index in childhood asthma

Most genome-wide association studies of obesity and body mass index (BMI) have so far assumed an additive mode of inheritance in their analysis, although association testing supports a recessive effect for some of the established loci, for example, rs1421085 in FTO In two whole-genome sequencing (WGS) studies of children with asthma and their parents (892 Costa Rican trios and 286 North American trios), we discovered an association between a locus (rs9292139) in LOC102724122 and BMI that reaches genome-wide significance under a recessive model in the combined analysis. As the association does not achieve significance under an additive model, our finding illustrates the benefits of the recessive model in WGS analyses.

M. S, Beyene Y, Das B, Prasanna BM, Gowda M. Discovery and Validation of a Recessively Inherited Major-Effect QTL Conferring Resistance to Maize Lethal Necrosis (MLN) Disease

Maize lethal necrosis (MLN) is a viral disease with a devastating effect on maize production. Developing and deploying improved varieties with resistance to the disease is important to effectively control MLN; however, little is known about the causal genes and molecular mechanism(s) underlying MLN resistance. Screening thousands of maize inbred lines revealed KS23-5 and KS23-6 as two of the most promising donors of MLN resistance alleles. KS23-5 and KS23-6 lines were earlier developed at the University of Hawaii, United States, on the basis of a source population constituted using germplasm from Kasetsart University, Thailand. Both linkage mapping and association mapping approaches were used to discover and validate genomic regions associated with MLN resistance. Selective genotyping of resistant and susceptible individuals within large F2 populations coupled with genome-wide association study identified a major-effect QTL (qMLN06_157) on chromosome 6 for MLN disease severity score and area under the disease progress curve values in all three F2 populations involving one of the KS23 lines as a parent. The major-effect QTL (qMLN06_157) is recessively inherited and explained 55%-70% of the phenotypic variation with an approximately 6 Mb confidence interval. Linkage mapping in three F3 populations and three F2 populations involving KS23-5 or KS23-6 as one of the parents confirmed the presence of this major-effect QTL on chromosome 6, demonstrating the efficacy of the KS23 allele at qMLN06.157 in varying populations. This QTL could not be identified in population that was not derived using KS23 lines. Validation of this QTL in six F2 populations with 20 SNPs closely linked with qMLN06.157 was further confirmed its consistent expression across populations and its recessive nature of inheritance. On the basis of the consistent and effective resistance afforded by the KS23 allele at qMLN06.157, the QTL can be used in both marker-assisted forward breeding and marker-assisted backcrossing schemes to improve MLN resistance of breeding populations and key lines for eastern Africa.

Associations of the SREBF2 Gene and INSIG2 Polymorphisms with Obesity and Dyslipidemia in Thai Psychotic Disorder Patients Treated with Risperidone

Background: Patients with psychotic disorders who receive atypical antipsychotic drugs often develop metabolic abnormalities. The sterol regulatory element-binding factor 2 (SREBF2) gene and insulin-induced gene (INSIG) have important roles in lipid metabolism. A previous study indicated that risperidone stimulated both lipogenesis and cholesterogenesis through activation of SREBP2 expression and inhibition of INSIG2. The SREBF2 gene and INSIG2 polymorphisms have been reported to be associated with metabolic abnormalities. Objective: To investigate the association of the SREBF2 gene (rs1052717, rs2267439, and rs2267443) and INSIG2 (rs7566605, rs11123469, and rs17587100) polymorphisms and the presence of obesity and dyslipidemia in Thai psychotic disorder patients treated with risperidone. Methods: All 113 psychiatric patients using risperidone were evaluated for their lipid profile and screened for obesity criteria. We genotyped the SREBF2 gene and INSIG2 polymorphisms using TaqMan real-time polymerase chain reaction. Results: None of the studied SREBF2 gene and INSIG2 SNPs were associated with obesity in Thai psychotic disorder patients receiving risperidone. Nonetheless, the SREBF2 rs2267443 (G/A) A-allele carriers were at a higher risk for hypertriglyceridemia, whereas the INSIG2 rs11123469 (T/C) C-allele carriers had a lower risk for hypertriglyceridemia, after being adjusted for clinical characteristics using multiple logistic regression. Conclusions: Our findings suggest that the SREBF2 gene rs2267443 (G/A) and the INSIG2 rs11123469 (T/C) polymorphisms are associated with dyslipidemia in Thai psychotic disorder patients treated with risperidone. Further studies with prospective designs and larger patient groups are needed.

Association of CNR1 and INSIG2 polymorphisms with antipsychotics-induced weight gain: a prospective nested case-control study

Weight gain is a frequent and severe adverse reaction in patients taking antipsychotics. The objective was to further investigate in a natural setting influential risk factors associated with clinically significant weight gain. An observational follow-up study was conducted. Patients when initiating treatment with whatever antipsychotic were included; a structured questionnaire was applied at baseline, 3 and 6 months later; a blood sample was obtained. In a nested case-control approach, patients with an increase ≥ 7% of their initial weight were considered as cases, the remaining, as controls. The results showed that, out of 185 patients, 137 completed the 6-month follow-up (cases, 38; controls, 99). Weight gain gradually and significantly increased in cases (baseline, 65.0 kg; 6 months, 74.0 kg) but not in controls (65.6 kg and 65.8 kg, respectively). Age (adjusted OR = 0.97, 95% CI = 0.96-0.99, p = 0.004), olanzapine (adjusted OR = 2.98, 95% CI = 1.13-7.80, p = 0.027) and quetiapine (adjusted OR = 0.25, 95% = 0.07-0.92, p = 0.037) significantly associated with weight gain. An association was also found for the CNR1 (rs1049353) and INSIG2 (rs7566605) polymorphisms. In conclusion, an increased risk of antipsychotics-induced weight gain was observed for younger age and olanzapine, and a relative lower risk for quetiapine. A potential role of CNR1 rs1049353 and INSIG2 rs7566605 polymorphisms is suggested.

Hidden Role of Gut Microbiome Dysbiosis in Schizophrenia: Antipsychotics or Psychobiotics as Therapeutics?

Schizophrenia is a chronic, heterogeneous neurodevelopmental disorder that has complex symptoms and uncertain etiology. Mounting evidence indicates the involvement of genetics and epigenetic disturbances, alteration in gut microbiome, immune system abnormalities, and environmental influence in the disease, but a single root cause and mechanism involved has yet to be conclusively determined. Consequently, the identification of diagnostic markers and the development of psychotic drugs for the treatment of schizophrenia faces a high failure rate. This article surveys the etiology of schizophrenia with a particular focus on gut microbiota regulation and the microbial signaling system that correlates with the brain through the vagus nerve, enteric nervous system, immune system, and production of postbiotics. Gut microbially produced molecules may lay the groundwork for further investigations into the role of gut microbiota dysbiosis and the pathophysiology of schizophrenia. Current treatment of schizophrenia is limited to psychotherapy and antipsychotic drugs that have significant side effects. Therefore, alternative therapeutic options merit exploration. The use of psychobiotics alone or in combination with antipsychotics may promote the development of novel therapeutic strategies. In view of the individual gut microbiome structure and personalized response to antipsychotic drugs, a tailored and targeted manipulation of gut microbial diversity naturally by novel prebiotics (non-digestible fiber) may be a successful alternative therapeutic for the treatment of schizophrenia patients.

Hidden Role of Gut Microbiome Dysbiosis in Schizophrenia: Antipsychotics or Psychobiotics as Therapeutics?

Schizophrenia is a chronic, heterogeneous neurodevelopmental disorder that has complex symptoms and uncertain etiology. Mounting evidence indicates the involvement of genetics and epigenetic disturbances, alteration in gut microbiome, immune system abnormalities, and environmental influence in the disease, but a single root cause and mechanism involved has yet to be conclusively determined. Consequently, the identification of diagnostic markers and the development of psychotic drugs for the treatment of schizophrenia faces a high failure rate. This article surveys the etiology of schizophrenia with a particular focus on gut microbiota regulation and the microbial signaling system that correlates with the brain through the vagus nerve, enteric nervous system, immune system, and production of postbiotics. Gut microbially produced molecules may lay the groundwork for further investigations into the role of gut microbiota dysbiosis and the pathophysiology of schizophrenia. Current treatment of schizophrenia is limited to psychotherapy and antipsychotic drugs that have significant side effects. Therefore, alternative therapeutic options merit exploration. The use of psychobiotics alone or in combination with antipsychotics may promote the development of novel therapeutic strategies. In view of the individual gut microbiome structure and personalized response to antipsychotic drugs, a tailored and targeted manipulation of gut microbial diversity naturally by novel prebiotics (non-digestible fiber) may be a successful alternative therapeutic for the treatment of schizophrenia patients.

The CC Genotype of Insulin-Induced Gene 2 rs7566605 Is a Protective Factor of Hypercholesteremia Susceptible to Mild Cognitive Impairment, Especially to the Executive Function of Patients with Type 2 Diabetes Mellitus

Methods

233 T2DM patients with MCI or without MCI were recruited. Baseline data and genotype frequency were compared between MCI and non-MCI groups. Demographic parameters and neuropsychological tests results were analyzed among patients with different genotypes. Further correlation and regression analysis were conducted to find the association between cognition and cholesterol.

Results

Despite no significant statistical difference was detected, we observed higher levels of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL) in patients with MCI than those without MCI. In addition, we observed higher TC and LDL levels in patients with GG or GC genotypes than those with CC genotype (P < 0.001, P = 0.004, or P < 0.001, P = 0.002). Interestingly, increased MoCA and decreased TMTB scores were found in patients with CC genotype, compared to those with GG or CG genotype (P = 0.009, P = 0.024, or P = 0.005, P = 0.109). Moreover, partial correlation (P = 0.030 and P = 0.004, respectively) and multiple linear regression (P = 0.030 and P = 0.005, respectively) showed that TC and LDL levels are associated with the TMTB score, indicating the executive function.

Conclusions

CC genotype of INSIG-2 rs7566605 may be a protective factor of hypercholesteremia susceptible to MCI, especially to the executive function of T2DM. This trial is registered with ChiCTROCC15006060.

The Genetic Basis of Obesity and Related Metabolic Diseases in Humans and Companion Animals

Obesity is one of the most prevalent health conditions in humans and companion animals globally. It is associated with premature mortality, metabolic dysfunction, and multiple health conditions across species. Obesity is, therefore, of importance in the fields of medicine and veterinary medicine. The regulation of adiposity is a homeostatic process vulnerable to disruption by a multitude of genetic and environmental factors. It is well established that the heritability of obesity is high in humans and laboratory animals, with ample evidence that the same is true in companion animals. In this review, we provide an overview of how genes link to obesity in humans, drawing on a wealth of information from laboratory animal models, and summarise the mechanisms by which obesity causes related disease. Throughout, we focus on how large-scale human studies and niche investigations of rare mutations in severely affected patients have improved our understanding of obesity biology and can inform our ability to interpret results of animal studies. For dogs, cats, and horses, we compare the similarities in obesity pathophysiology to humans and review the genetic studies that have been previously reported in those species. Finally, we discuss how veterinary genetics may learn from humans about studying precise, nuanced phenotypes and implementing large-scale studies, but also how veterinary studies may be able to look past clinical findings to mechanistic ones and demonstrate translational benefits to human research.

Response to Comments on "A Common Genetic Variant Is Associated with Adult and Childhood Obesity"

Identification of genetic variants affecting complex traits such as obesity is confounded by many types of bias, especially when effect sizes are small. Given our findings of a positive association between rs7566605 and body mass index in four out of five separate samples, a false positive finding cannot be ruled out with certainty but seems unlikely. Meta-analyses of multiple large studies will help refine the estimate of the effects of rs7566605 on body mass index.

Precision Health: The Role of the Social and Behavioral Sciences in Advancing the Vision

BACKGROUND

In 2015, Collins and Varmus articulated a vision for precision medicine emphasizing molecular characterization of illness to identify actionable biomarkers to support individualized treatment. Researchers have argued for a broader conceptualization, precision health. Precision health is an ambitious conceptualization of health, which includes dynamic linkages between research and practice as well as medicine, population health, and public health. The goal is a unified approach to match a full range of promotion, prevention, diagnostic, and treatment interventions to fundamental and actionable determinants of health; to not just address symptoms, but to directly target genetic, biological, environmental, and social and behavioral determinants of health.

PURPOSE

The purpose of this paper is to elucidate the role of social and behavioral sciences within precision health.

MAIN BODY

Recent technologies, research frameworks, and methods are enabling new approaches to measure, intervene, and conduct social and behavioral science research. These approaches support three opportunities in precision health that the social and behavioral sciences could colead including: (a) developing interventions that continuously "tune" to each person's evolving needs; (b) enhancing and accelerating links between research and practice; and (c) studying mechanisms of change in real-world contexts. There are three challenges for precision health: (a) methods of knowledge organization and curation; (b) ethical conduct of research; and (c) equitable implementation of precision health.

CONCLUSIONS

Precision health requires active coleadership from social and behavioral scientists. Prior work and evidence firmly demonstrate why the social and behavioral sciences should colead with regard to three opportunity and three challenge areas.

Genetic Determinants of Childhood Obesity

Obesity represents a major health burden to both developed and developing countries. Furthermore, the incidence of obesity is increasing in children. Obesity contributes substantially to mortality in the United States by increasing the risk for type 2 diabetes, cardiovascular-related diseases, and other comorbidities. Despite environmental changes over past decades, including increases in high-calorie foods and sedentary lifestyles, there is very clear evidence of a genetic predisposition to obesity risk. Childhood obesity cases can be categorized in one of two ways: syndromic or non-syndromic. Syndromic obesity includes disorders such as Prader-Willi syndrome, Bardet-Biedl syndrome, and Alström syndrome. Non-syndromic cases of obesity can be further separated into rarer instances of monogenic obesity and much more common forms of polygenic obesity. The advent of genome-wide association studies (GWAS) and next-generation sequencing has driven significant advances in our understanding of the genetic contribution to childhood obesity. Many rare and common genetic variants have been shown to contribute to the heritability in obesity, although the molecular mechanisms underlying most of these variants remain unclear. An important caveat of GWAS efforts is that they do not strictly represent gene target discoveries, rather simply the uncovering of robust genetic signals. One clear example of this is with progress in understanding the key obesity signal harbored within an intronic region of the FTO gene. It has been shown that the non-coding region in which the variant actually resides in fact influences the expression of genes distal to FTO instead, specifically IRX3 and IRX5. Such discoveries suggest that associated non-coding variants can be embedded within or next to one gene, but commonly influence the expression of other, more distal effector genes. Advances in genetics and genomics are therefore contributing to a deeper understanding of childhood obesity, allowing for development of clinical tools and therapeutic agents.

Longitudinal analysis reveals transition barriers between dominant ecological states in the gut microbiome

Deep molecular phenotyping of individuals provides the opportunity for biological insight into host physiology. As the human microbiome is increasingly being recognized as an important determinant of host health, understanding the host–microbiome relationship in a multiomics context may pave the way forward for targeted interventions. In this study, we analyze gut microbial composition of 101 individuals over the course of a year, alongside clinical markers and serum metabolomics. We establish association between specific gut compositional states and host health biomarkers (e.g., of inflammation). Finally, we provide evidence for an apparent transition barrier between these compositional states. A deeper understanding of microbiome dynamics and the associated variation in host phenotypes furthers our ability to engineer effective interventions that optimize wellness.

The Pioneer 100 Wellness Project involved quantitatively profiling 108 participants’ molecular physiology over time, including genomes, gut microbiomes, blood metabolomes, blood proteomes, clinical chemistries, and data from wearable devices. Here, we present a longitudinal analysis focused specifically around the Pioneer 100 gut microbiomes. We distinguished a subpopulation of individuals with reduced gut diversity, elevated relative abundance of the genus Prevotella, and reduced levels of the genus Bacteroides. We found that the relative abundances of Bacteroides and Prevotella were significantly correlated with certain serum metabolites, including omega-6 fatty acids. Primary dimensions in distance-based redundancy analysis of clinical chemistries explained 18.5% of the variance in bacterial community composition, and revealed a Bacteroides/Prevotella dichotomy aligned with inflammation and dietary markers. Finally, longitudinal analysis of gut microbiome dynamics within individuals showed that direct transitions between Bacteroides-dominated and Prevotella-dominated communities were rare, suggesting the presence of a barrier between these states. One implication is that interventions seeking to transition between Bacteroides- and Prevotella-dominated communities will need to identify permissible paths through ecological state-space that circumvent this apparent barrier.

Association of PCSK1 gene polymorphisms with abdominal fat content in broilers

Protein proteolytic enzymes (Proprotein Convertase, PC) is a Ca²⁺ -dependent serine protease family, whose main function is to cleave precursors of biologically inactive proteins or peptide chains into active functional molecules. Proprotein convertase subtilisin/kexin type 1 (PCSK1) gene is mainly expressed in nerve and endocrine tissues. In this study, PCSK1 was selected as an important candidate gene for abdominal fat content in broilers. We cloned the exon region of chicken PCSK1 gene and found six single-nucleotide polymorphisms (SNPs). Association analysis was carried out and we found that the polymorphisms of these six SNPs were significantly associated with abdominal fat content in G19 and G20 populations. Five of these SNPs were significantly associated with abdominal fat content in G19 and G20 combined population. The polymorphism of these five SNPs was significantly correlated with the abdominal fat content of AA broilers. Together, our study demonstrated that c.927T>C, c.1880C>T, c.*900G>A, and c.*1164C>T were significantly associated with abdominal fat content in populations used in this study, which means that these SNPs in PCSK1 gene could be used as candidate markers to select lean broiler lines.

The connection between microbiome and schizophrenia

There has been an accumulation of knowledge about the human microbiome, some detailed investigations of the gastrointestinal microbiota and its functions, and the highlighting of complex interactions between the gut, the gut microbiota, and the central nervous system. That assumes the involvement of the microbiome in the pathogenesis of various CNS diseases, including schizophrenia. Given this information and the fact, that the gut microbiota is sensitive to internal and environmental influences, we have speculated that among the factors that influence the formation and composition of gut microbiota during life, possible key elements in the schizophrenia development chain are hidden where gut microbiota is a linking component. This article aims to describe and understand the developmental relationships between intestinal microbiota and the risk of developing schizophrenia.

Adiponectin Expression and Genotypes in Italian People with Severe Obesity Undergone a Hypocaloric Diet and Physical Exercise Program

Adiponectin exerts positive effects on metabolic and inflammatory processes. Adiponectin levels and some single-nucleotide polymorphisms (SNPs) seem to be associated with obesity. Here, we investigated the effects of a 4-week Hypocaloric diet and Physical exercise Program (HPP) on 268 young people with severe obesity. We evaluated the relationship between adiponectin levels and anthropometric and biochemical parameters, at baseline and after a 4-week HPP. Finally, we investigated some adiponectin gene variants and their correlation to biochemical parameters. Adiponectin levels were statistically lower in people with severe obesity than in controls. At the end of the HPP, all the people with severe obesity showed a Body Mass Index (BMI) reduction with a statistically significant increase in adiponectin levels. Genotyping, the adiponectin gene demonstrated a significant difference in 3 polymorphisms within the people with severe obesity. Besides, c.11377C>G and c.11391G>A homozygous subjects experienced more advantages by HPP. Furthermore, c.268G>A heterozygous subjects showed an enhancement in lipid profile as well in adiponectin levels. The best predictor of the changes in adiponectin levels was represented by the c.268G>A WT allele. Our study confirmed that a 4-weeks HPP in people with severe obesity results in metabolic amelioration associated with a significant increase of adiponectin levels. Importantly, we found that a specific genetic background in the ADIPOQ gene can predispose toward a more significant weight loss.

MC4R variants rs12970134 and rs17782313 are associated with obese polycystic ovary syndrome patients in the Western region of Saudi Arabia

BACKGROUND

Polycystic ovary syndrome (PCOS) is a common endocrine disorder causing infertility in reproductive-age women. The cause of PCOS is not fully understood but it is thought to be influenced by environmental and genetic factors. Obesity is greatly related to PCOS and its reduction is one of the major aims in treating PCOS. Melanocortin 4 receptor (MC4R) gene polymorphisms were detected to be associated with different levels of obesity. Therefore, we aimed to determine the genotype and allele frequency of MC4R variants rs12970134 (A/G) and rs17782313 (C/T) in PCOS and investigate their association with PCOS and its clinical variables.

METHODS

A case-control study was conducted on 189 women, consisting of 95 PCOS cases and 94 controls. Genotyping was performed by real-time polymerase chain reaction (PCR) using TaqMan™ Genotyping assays. Quantitative data were presented as (median ± interquartile range (IQR) whereas qualitative data were presented as frequencies. The chi-squared test was used to observe the difference between SNPs within the study groups (PCOS and control subjects). Multinomial logistic regression was used to test the risk of obesity and development of PCOS considering p < 0.05 is statistically significant.

RESULTS

Rs12970134 and rs17782313 are significantly associated with body mass index (BMI, kg/m², p < 0.0001) in PCOS women but not associated with PCOS itself. Risk alleles in our population are A in rs12970134 and C in rs17782313 that are associated with high BMI (> 30 kg/m²) in obese women with PCOS (OR = 1.348, p = 0.002 and OR = 1.364, p = 0.002 respectively) in the homozygous state. In addition, we found that the other genotypes for non-obese PCOS group, AG/GG for rs12970134 and CT/TT for rs17782313, are associated with hirsutism, loss of hair, hyperandrogenism and anti-Müllerian hormone in PCOS.

CONCLUSIONS

These findings demonstrate that MC4R single nucleotide polymorphisms, rs12970134 and rs17782313, are correlated with elevated BMI in PCOS but are not causative factors for PCOS among women in the western region of Saudi Arabia. Moreover, the reverse genotypes are associated with major clinical variants in non-obese (< 30 kg/m²) PCOS patients may demonstrate a poor prognosis for this group.

A Cautionary Note on the Effects of Population Stratification Under an Extreme Phenotype Sampling Design

Extreme phenotype sampling (EPS) is a popular study design used to reduce genotyping or sequencing costs. Assuming continuous phenotype data are available on a large cohort, EPS involves genotyping or sequencing only those individuals with extreme phenotypic values. Although this design has been shown to have high power to detect genetic effects even at smaller sample sizes, little attention has been paid to the effects of confounding variables, and in particular population stratification. Using extensive simulations, we demonstrate that the false positive rate under the EPS design is greatly inflated relative to a random sample of equal size or a “case-control”-like design where the cases are from one phenotypic extreme and the controls randomly sampled. The inflated false positive rate is observed even with allele frequency and phenotype mean differences taken from European population data. We show that the effects of confounding are not reduced by increasing the sample size. We also show that including the top principal components in a logistic regression model is sufficient for controlling the type 1 error rate using data simulated with a population genetics model and using 1,000 Genomes genotype data. Our results suggest that when an EPS study is conducted, it is crucial to adjust for all confounding variables. For genetic association studies this requires genotyping a sufficient number of markers to allow for ancestry estimation. Unfortunately, this could increase the costs of a study if sequencing or genotyping was only planned for candidate genes or pathways; the available genetic data would not be suitable for ancestry correction as many of the variants could have a true association with the trait.

Heterozygous rare genetic variants in non-syndromic early-onset obesity

BACKGROUND

Obesity is a very heterogeneous disorder at both the clinical and molecular levels and with high heritability. Several monogenic forms and genes with strong effects have been identified for non-syndromic severe obesity. Novel therapeutic interventions are in development for some genetic forms, emphasizing the importance of determining genetic contributions.

OBJECTIVE

We aimed to define the contribution of rare single-nucleotide genetic variants (RSVs) in candidate genes to non-syndromic severe early-onset obesity (EOO; body mass index (BMI) >+3 standard deviation score, <3 years).

METHODS

Using a pooled DNA-sequencing approach, we screened for RSVs in 15 obesity candidate genes in a series of 463 EOO patients and 480 controls. We also analysed exome data from 293 EOO patients from the "Viva la Familia" (VLF) study as a replication dataset.

RESULTS

Likely or known pathogenic RSVs were identified in 23 patients (5.0%), with 7 of the 15 genes (BDNF, FTO, MC3R, MC4R, NEGR1, PPARG and SIM1) harbouring RSVs only in cases (3.67%) and none in controls. All were heterozygous changes, either de novo (one in BDNF) or inherited from obese parents (seven maternal, three paternal), and no individual carried more than one variant. Results were replicated in the VLF study, where 4.10% of probands carried RSVs in the overrepresented genes. RSVs in five genes were either absent (LEP) or more common in controls than in cases (ADRB3, LEPR, PCSK1 and PCSK2) in both obese datasets.

CONCLUSIONS

Heterozygous RSVs in several candidate genes of the melanocortin pathway are found in ~5.0% patients with EOO. These results support the clinical utility of genetic testing to identify patients who might benefit from targeted therapeutic intervention.

Pharmacogenetic Correlates of Antipsychotic-Induced Weight Gain in the Chinese Population

Antipsychotic-induced weight gain (AIWG) is a common adverse effect of this treatment, particularly with second-generation antipsychotics, and it is a major health problem around the world. We aimed to review the progress of pharmacogenetic studies on AIWG in the Chinese population to compare the results for Chinese with other ethnic populations, identify the limitations and problems of current studies, and provide future research directions in China. Both English and Chinese electronic databases were searched to identify eligible studies. We determined that > 25 single-nucleotide polymorphisms in 19 genes have been investigated in association with AIWG in Chinese patients over the past few decades. HTR2C rs3813929 is the most frequently studied single-nucleotide polymorphism, and it seems to be the most strongly associated with AIWG in the Chinese population. However, many genes that have been reported to be associated with AIWG in other ethnic populations have not been included in Chinese studies. To explain the pharmacogenetic reasons for AIWG in the Chinese population, genome-wide association studies and multiple-center, standard, unified, and large samples are needed.

The ethnobotanical domain of the Swat Valley, Pakistan

BACKGROUND

This study contributes to the current ethnomedicinal knowledge of the Swat Valley, Pakistan. District Swat possesses remarkable biodiversity owing to its varied topographical and climatic conditions, prompting a distinct human-plant association. Our hypothesis is that the presence of such a great biodiversity has shaped into a formal ethnobotanical culture in the area transmitted through generations. We suspect that the versatility of some plant species has greater influence on the culture. Therefore, the prime objective of the study is to understand this unique human-plant relationship in the valley and to create scientific roots for the selection and practice of herbs in the ethnobotanical domain of the district.

METHODS

Primary data were collected using questionnaires and face-to-face interviews with the locals. The data collected were used for calculating some important indices, i.e. relative frequency of citation (RFC), participant agreement ratio (PAR), frequency of citation (FC), Smith's Salience Index (SI), Relative Importance Index (RII), Cultural Value Index (CVI) and a newly proposed, Ali's Conservation Priority Index (CPI). Index scores were used as key identifier of the ethnobotanically important plants of the area.

RESULTS

Residents of the Swat Valley have listed plant uses in 15 use categories. Around 9% of the respondents have a common consensus on the selection and use of plants for the treatment of evil eye with similar results for body cuts (8.2%) followed by psychological/neural ailments (8.0%). Respondents agree that Berberis lyceum Royle. dominates in all five indices. Skimmia laureola Franch. also constitutes one of the central plants of the ethnobotanical domain, ranking second in the SI, fifth in the RII, seventh in CVI, and third in the Cultural Importance Index. It holds the thirty-fifth position in the CPI. Over 80% of the population treat different diseases with herbal remedies. In the common ethnobotanical domain of the area, plants like Mentha longifolia L., Berberis lyceum, and Skimmia laureola are very important and have high salience and importance values, thus suggesting these plants are versatile for their uses in the study area.

CONCLUSION

In conclusion, only some plant species are prioritised for their use in the ethnobotanical domain of the community. Medicinal and aromatic plant (MAP) usage is widespread in the Swat Valley. The ethnobotanical knowledge could be used as a tool to understand the adaptability of a specific taxon in the area and the possible conservation risk to their existence.

Identification of a potential functional single nucleotide polymorphism for fatness and growth traits in the 3'-untranslated region of the PCSK1 gene in chickens

Prohormone convertase 1/3 is a serine endoprotease belonging to the subtilisin-like proprotein convertase family that is encoded by the () gene, and its major function is the processing and bioactivation of the proproteins of many kinds of neuroendocrine hormones, including insulin, cholecystokinin, and adrenocorticotropic hormone. The results of our previous genomewide association study indicated that the gene might be an important candidate gene for fatness traits in chickens. The objectives of this study were to investigate the tissue expression profiles of gene and to identify functional variants associated with fatness and growth traits in the chicken. The results indicated that mRNA was widely expressed in various tissues, especially neuroendocrine and intestinal tissues. Of these 2 tissue types, mRNA expression in lean males was significantly higher than in fat males. A SNP in the 3' untranslated region of (c.*900G > A) was identified. Association analysis in the Arbor Acres commercial broiler population and Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF) population showed that the SNP c.*900G > A was associated with abdominal fat weight, abdominal fat percentage, BW, metatarsus length, and metatarsal circumference. In the 5th to 19th generation (G to G) of NEAUHLF, the allele frequency of c.*900G > A changed along with selection for abdominal fat content. At G, allele G of c.*900G > A was predominate in the lean line, whereas allele A was predominate in the fat line. Functional analysis demonstrated that allele A of c.*900G > A reduced mRNA stability and consequently downregulated gene expression. These results suggested that c.*900G > A was a functional SNP for fatness and growth traits in the chicken. The results of this study provide basic molecular information for the role of gene in avian growth and development, especially obesity.

MetaGen: reference-free learning with multiple metagenomic samples

A major goal of metagenomics is to identify and study the entire collection of microbial species in a set of targeted samples. We describe a statistical metagenomic algorithm that simultaneously identifies microbial species and estimates their abundances without using reference genomes. As a trade-off, we require multiple metagenomic samples, usually ≥10 samples, to get highly accurate binning results. Compared to reference-free methods based primarily on k-mer distributions or coverage information, the proposed approach achieves a higher species binning accuracy and is particularly powerful when sequencing coverage is low. We demonstrated the performance of this new method through both simulation and real metagenomic studies. The MetaGen software is available at https://github.com/BioAlgs/MetaGen.

Childhood maltreatment and high dietary fat intake behaviors in adulthood: A birth cohort study

Childhood maltreatment has been associated with a wide range of chronic medical conditions including obesity, other metabolic events and eating disorders. However, little is known about the association between childhood maltreatment and high dietary fat intake. This study addresses the extent to which co-occurring and specific forms of substantiated childhood maltreatment are associated with self-reported high dietary fat intake in adulthood and whether there is a gender-childhood maltreatment interaction in predicting this association. The study also examines the association between age at substantiation of maltreatment, number of childhood maltreatment substantiations and high dietary fat intake-related behaviors. The data were from a prospective Australian pre-birth mother-child dyads study, the Mater-University of Queensland Study of Pregnancy. The study followed 7223 mother-child dyads following the birth of a live, singleton baby at the Mater hospital. Recruitment was early in pregnancy, and then follow-ups at 3-5days postpartum and again when the child was 6 months, 5, 14 and 21 years of age. The data were linked to agency-substantiated cases of childhood maltreatment 0-14 years. This study extended the data linkage to 3766 (47.4% female) participants who had complete data on dietary fat intake behaviors at the 21-year follow-up. Consecutive logistic regressions were used to estimate odds ratios with respective 95% confidence intervals for high dietary fat intake for multiple and specific forms of childhood maltreatment, as well as age at and number of childhood maltreatment substantiations. Finally, a gender-childhood maltreatment interaction term was used to predict the outcome. In both unadjusted and adjusted analyses, substantiated childhood maltreatment including physical abuse were associated with high dietary fat intake-related behaviors. Similarly, substantiation of childhood maltreatment between the ages of 5 and 14 years was significantly associated with high dietary fat intake-related behaviors as were two or more substantiations of maltreatment. Inclusion of gender-childhood maltreatment interaction only had a minor impact on the size and direction of the association. Chronic and severe forms of childhood maltreatment including physical abuse are associated with a higher rate of dietary fat intake in young adulthood. Further research to replicate this association might focus on possible neuro-hormonal mechanisms that might explain this behavior.

Overexpression of Insig-2 inhibits atypical antipsychotic-induced adipogenic differentiation and lipid biosynthesis in adipose-derived stem cells

Atypical antipsychotics (AAPs) are considered to possess superior efficacy for treating both the positive and negative symptoms of schizophrenia; however, AAP use often causes excessive weight gain and metabolic abnormalities. Recently, several reports have demonstrated that AAPs activate sterol regulatory element-binding protein (SREBP). SREBP, SREBP cleavage-activating protein (SCAP) and insulin-induced gene (Insig) regulate downstream cholesterol and fatty acid biosynthesis. In this study, we explored the effects of clozapine, olanzapine and risperidone on SREBP signaling and downstream lipid biosynthesis genes in the early events of adipogenic differentiation in adipose-derived stem cells (ASCs). After the induction of adipogenic differentiation for 2 days, all AAPs, notably clozapine treatment for 3 and 7 days, enhanced the expression of SREBP-1 and its downstream lipid biosynthesis genes without dexamethasone and insulin supplementation. Simultaneously, protein level of SREBP-1 was significantly enhanced via inhibition of Insig-2 expression. By contrast, SREBP-1 activation was suppressed when Insig-2 expression was upregulated by transfection with Insig-2 plasmid DNA. In summary, our results indicate that AAP treatment, notably clozapine treatment, induces early-stage lipid biosynthesis in ASCs. Such abnormal lipogenesis can be reversed when Insig-2 expression was increased, suggesting that Insig/SCAP/SREBP signaling may be a therapeutic target for AAP-induced weight gain and metabolic abnormalities.

Two obesity susceptibility loci in LYPLAL1 and ETV5 independently associated with childhood hypertension in Chinese population

AIMS

Genome-wide association studies have identified novel obesity-associated susceptibility loci. Associations of these variants with childhood obesity have been studied in our previous research. The purpose of this study is to investigate if these loci are associated with hypertension being independent of obesity in Chinese children and adolescents.

METHODS

Nineteen candidate SNPs were genotyped using Sequenom MassARRAY platform among Chinese children (N=2954, 514 hypertension and 2440 controls, aged 7-17years). Dietary behaviors were assessed through face to face investigations.

RESULTS

Of the nineteen obese related SNPs, ten SNPs were found to be associated with systolic blood pressure (SBP) or diastolic blood pressure (DBP) in Chinese children. After adjusting for age, sex and WHtR, rs2605100 in LYPLAL1was found to be associated with high blood pressure (HBP) under dominant model (P=0.024) with the OR of 1.274 (95% CI =1.033-1.572, effect genotype=GG). The distribution of genotype of rs7647305 in ETV5 showed significant difference between HBP and non-HBP subjects under dominant model (P=0.011) with the OR of 0.654 (95% CI=0.471-0.909, effect genotype=CC). Using rs2605100 and rs7647305, the genetic risk score (GRS) analysis showed that, after adjusted for age, sex and WHtR, subjects carrying one or two risk alleles had the risks of hypertension with the ORs 1.797 (95% CI, 1.168-2.765), 2.149 (95% CI, 1.375-3.357) comparing with the subjects with non-risk-allele.

CONCLUSIONS

Genetic variations of obesity-associated loci, LYPLAL1 rs2605100 and ETV5 rs7647305 independently associate with the risk of childhood hypertension in China.

Epidemiology in Germany-general development and personal experience

Did you ever hear about epidemiology in Germany? Starting from an epidemiological desert the discipline has grown remarkably, especially during the last 10-15 years: research institutes have been established, research funding has improved, multiple curriculae in Epidemiology and Public Health are offered. This increase has been quite steep, and now the epidemiological infrastructure is much better. Several medium-sized and even big population cohorts are ongoing, and the number and quality of publications from German epidemiologists has reached a respectable level. My own career in epidemiology started in the field of environmental health. After German reunification I concentrated for many years on environmental problems in East Germany and observed the health benefits after improvement of the situation. Later, I concentrated on population-based cohorts in newborns (GINI/LISA) and adults (KORA, German National Cohort), and on biobanking. This Essay describes the development in Germany after worldwar 2, illustrated by examples of research results and build-up of epidemiological infractructures worth mentioning.

The microbiome in early life: implications for health outcomes

Recent studies have characterized how host genetics, prenatal environment and delivery mode can shape the newborn microbiome at birth. Following this, postnatal factors, such as antibiotic treatment, diet or environmental exposure, further modulate the development of the infant's microbiome and immune system, and exposure to a variety of microbial organisms during early life has long been hypothesized to exert a protective effect in the newborn. Furthermore, epidemiological studies have shown that factors that alter bacterial communities in infants during childhood increase the risk for several diseases, highlighting the importance of understanding early-life microbiome composition. In this review, we describe how prenatal and postnatal factors shape the development of both the microbiome and the immune system. We also discuss the prospects of microbiome-mediated therapeutics and the need for more effective approaches that can reconfigure bacterial communities from pathogenic to homeostatic configurations.

The association of insertions/deletions (INDELs) and variable number tandem repeats (VNTRs) with obesity and its related traits and complications

BACKGROUND

Despite the fact that insertions/deletions (INDELs) are the second most common type of genetic variations and variable number tandem repeats (VNTRs) represent a large portion of the human genome, they have received far less attention than single nucleotide polymorphisms (SNPs) and larger forms of structural variation like copy number variations (CNVs), especially in genome-wide association studies (GWAS) of complex diseases like polygenic obesity. This is exemplified by the vast amount of review papers on the role of SNPs and CNVs in obesity, its related traits (like anthropometric measurements, biochemical variables, and eating behavior), and its related complications (like hypertension, hypertriglyceridemia, hypercholesterolemia, and insulin resistance-collectively known as metabolic syndrome). Hence, this paper reviews the types of INDELs and VNTRs that have been studied for association with obesity and its related traits and complications. These INDELs and VNTRs could be found in the obesity loci or genes from the earliest GWAS and candidate gene association studies, like FTO, genes in the leptin-proopiomelanocortin pathway, and UCP2/3. Given the important role of the brain serotonergic and dopaminergic reward system in obesity susceptibility, the association of INDELs and VNTRs in these neurotransmitters' metabolism and transport genes with obesity is also reviewed. Next, the role of INS VNTR in obesity and its related traits is questionable, since recent large-scale studies failed to replicate the earlier positive associations. As obesity results in chronic low-grade inflammation of the adipose tissue, the proinflammatory cytokine gene IL1RA and anti-inflammatory cytokine gene IL4 have VNTRs that are implicated in obesity. A systemic proinflammatory state in combination with activation of the renin-angiotensin system and decreased nitric oxide bioavailability as found in obesity leads to endothelial dysfunction. This explains why VNTR and INDEL in eNOS and ACE, respectively, could be predisposing factors of obesity. Finally, two novel genes, DOCK5 and PER3, which are involved in the regulation of the Akt/MAPK pathway and circadian rhythm, respectively, have VNTRs and INDEL that might be associated with obesity.

SHORT CONCLUSION

In conclusion, INDELs and VNTRs could have important functional consequences in the pathophysiology of obesity, and research on them should be continued to facilitate obesity prediction, prevention, and treatment.

Common Genetic Variant of insig2 Gene rs7566605 Polymorphism Is Associated with Severe Obesity in North India

Background:

Obesity is a very common disorder resulting from an imbalance between food intake and energy expenditure, and it has a substantial impact on the development of chronic diseases. The aim of this study was to examine the association of INSIG2 (rs7566605) gene polymorphism with obesity and obesity associated phenotypes in North Indian subjects.

Methods:

The variants were investigated for association in 642 obese and non-obese individuals. The genotyping of INSIG2 (rs7566605) single nucleotide polymorphism was analyzed by the TaqMan allelic discrimination protocol.

Results:

A significant association was observed for INSIG2 (rs7566605) single nucleotide polymorphism with obesity and obesity-related phenotypes. Furthermore, a significant relationship was found between the rs7566605 and insulin, homeostasis model of assessment-insulin resistance, the percentage of body fat, fat mass, leptin, and adiponectin.

Conclusion:

The present study observed significant association between INSIG2 (rs7566605) single nucleotide polymorphism and obesity, as well as obesity-associated phenotypes in North Indian population.

Construct Validity of an Obesity Risk Screening Tool in Two Age Groups

Home environment influences child health, but the impact varies as children move into adolescence. The Family Nutrition and Physical Activity (FNPA) screening tool has been used to evaluate home environments, but studies have not compared the utility of the tool in different age groups. The purpose of this study was to examine the efficacy of the FNPA tool in first and tenth grade samples. Parents of first grade (n = 250) and tenth grade (n = 99) students completed the FNPA and results were linked to body mass index (BMI) data. FNPA scores were examined by gender, income, race, and school-level socioeconomic status (SES). Correlations examined associations between FNPA scores and several BMI indicators. Logistic and linear regression analyses evaluated the construct validity of the FNPA in both groups. Mean FNPA score differed by age group, by SES in both age groups, and by race in the first grade sample only. Correlations between FNPA score and BMI indicators were higher in the first grade sample, but SES was significantly associated with BMI only in tenth graders. The FNPA has stronger utility in younger children, while school SES is a stronger predictor of adolescent weight status.

Organized sport and physical activity participation and body mass index in children and youth: A longitudinal study

The relationship between sport participation and BMI in children and adolescents is unclear, with some studies showing no association at all and others suggesting that sport is linked to lower BMI. Another possibility, however, is that this relationship is bidirectional, with sport leading to lower BMI but BMI also influencing sport participation. Here, we examine the direction of this association by analyzing a longitudinal dataset. Data come from the Physical Health Activity Study Team (PHAST) study, a prospective open cohort study including 2278 children at baseline, followed from 2004 to 2010. We fit 3 lagged mixed effects models: One examining the simultaneous relationship, one regressing past BMI on present sport participation, and one regressing sport participation on present BMI. Our baseline sample included 1999 children, of whom 50% were female. Mean BMI increased over the study period from 19.0 (SD = 3.7) to 21.2 (SD = 4.1), while organized sport participation declined. Model results showed that BMI and sport are weakly associated, and that each of these variables predicts the other, which generally supports a bidirectional relationship. Consistent with some previous reports, however, the effect size in both directions is very small. At the levels of participation in our sample, activity and BMI are very weakly related. Findings should not obscure the other benefits of physical activity.

Association Study of Three Gene Polymorphisms Recently Identified by a Genome-Wide Association Study with Obesity-Related Phenotypes in Chinese Children

OBJECTIVE

This study aimed to examine associations of three single-nucleotide polymorphisms (SNPs) with obesity-related phenotypes in Chinese children. These SNPs were identified by a recent genome-wide association (GWA) study among European children. Given that varied genetic backgrounds across different ethnicity may result in different association, it is necessary to study these associations in a different ethnic population.

METHODS

A total of 3,922 children, including 2,191 normal-weight, 873 overweight and 858 obese children, from three independent studies were included in the study. Logistic and linear regressions were performed, and meta-analyses were conducted to assess the associations between the SNPs and obesity-related phenotypes.

RESULTS

The pooled odds ratios of the A-allele of rs564343 in PACS1 for obesity and severe obesity were 1.180 (p = 0.03) and 1.312 (p = 0.004), respectively. We also found that rs564343 was nominally associated with BMI, BMI standard deviation score (BMI-SDS), waist circumference, and waist-to-height ratio (p < 0.05).

CONCLUSIONS

We showed for the first time that the rs564343 in PACS1 was associated with risk of severe obesity in a non-European population. This SNP was also found to be associated with common obesity and various obesity-related phenotypes in Chinese children, which had not been reported in the original study. The results demonstrated the value of conducting genetic researches in populations with different ethnicity.

INSIG2 polymorphism and weight gain, dyslipidemia and serum adiponectin in Finnish patients with schizophrenia treated with clozapine

Aim: To investigate INSIG2's association with obesity, weight change and serum lipid profile during clozapine treatment. Materials & methods: Subjects with schizophrenia (n = 190) were genotyped, identifying seven SNPs. Genetic risk scores (GRSs) were calculated to adiponectin, high-density lipoprotein cholesterol, triglycerides and weight gain. Results: In the model for weight gain, SNPs rs12151787, rs17047733 and rs10490626 were selected. Explanatory variables were BMI (p = 5.05 × 10-5), age (p = 0.003) and GRS (p = 2.81 × 10-5, p = 0.0002 after permutation). No GRS resulted for adiponectin or high-density lipoprotein cholesterol. Rs2161829 and rs10490620 were selected for triglycerides; this GRS was insignificant after permutation. Conclusion: INSIG2 plays a role in weight gain and obesity during clozapine treatment.

An algorithm for direct causal learning of influences on patient outcomes

OBJECTIVE

This study aims at developing and introducing a new algorithm, called direct causal learner (DCL), for learning the direct causal influences of a single target. We applied it to both simulated and real clinical and genome wide association study (GWAS) datasets and compared its performance to classic causal learning algorithms.

METHOD

The DCL algorithm learns the causes of a single target from passive data using Bayesian-scoring, instead of using independence checks, and a novel deletion algorithm. We generate 14,400 simulated datasets and measure the number of datasets for which DCL correctly and partially predicts the direct causes. We then compare its performance with the constraint-based path consistency (PC) and conservative PC (CPC) algorithms, the Bayesian-score based fast greedy search (FGS) algorithm, and the partial ancestral graphs algorithm fast causal inference (FCI). In addition, we extend our comparison of all five algorithms to both a real GWAS dataset and real breast cancer datasets over various time-points in order to observe how effective they are at predicting the causal influences of Alzheimer's disease and breast cancer survival.

RESULTS

DCL consistently outperforms FGS, PC, CPC, and FCI in discovering the parents of the target for the datasets simulated using a simple network. Overall, DCL predicts significantly more datasets correctly (McNemar's test significance: p<<0.0001) than any of the other algorithms for these network types. For example, when assessing overall performance (simple and complex network results combined), DCL correctly predicts approximately 1400 more datasets than the top FGS method, 1600 more datasets than the top CPC method, 4500 more datasets than the top PC method, and 5600 more datasets than the top FCI method. Although FGS did correctly predict more datasets than DCL for the complex networks, and DCL correctly predicted only a few more datasets than CPC for these networks, there is no significant difference in performance between these three algorithms for this network type. However, when we use a more continuous measure of accuracy, we find that all the DCL methods are able to better partially predict more direct causes than FGS and CPC for the complex networks. In addition, DCL consistently had faster runtimes than the other algorithms. In the application to the real datasets, DCL identified rs6784615, located on the NISCH gene, and rs10824310, located on the PRKG1 gene, as direct causes of late onset Alzheimer's disease (LOAD) development. In addition, DCL identified ER category as a direct predictor of breast cancer mortality within 5 years, and HER2 status as a direct predictor of 10-year breast cancer mortality. These predictors have been identified in previous studies to have a direct causal relationship with their respective phenotypes, supporting the predictive power of DCL. When the other algorithms discovered predictors from the real datasets, these predictors were either also found by DCL or could not be supported by previous studies.

CONCLUSION

Our results show that DCL outperforms FGS, PC, CPC, and FCI in almost every case, demonstrating its potential to advance causal learning. Furthermore, our DCL algorithm effectively identifies direct causes in the LOAD and Metabric GWAS datasets, which indicates its potential for clinical applications.