Putting the Genome in Context: Gene-Environment Interactions in Type 2 Diabetes

The Landscape of Direct-To-Consumer Genetic Testing in Reproductive Health Contexts: An Analytical Framework of Stakeholders and Their Competing Motivations

We propose a theoretical framework that identifies (a) the different categories of stakeholders and (b) the normative values that drive their attitudes toward direct-to-consumer genetic testing, with an emphasis on the reproductive health contexts. We conducted a literature search using varied combinations of search terms, including direct-to-consumer genetic testing, decision-making, reproductive health, and policy. Using a grounded theory approach to existing literature and in combination with a narrative review, we present a systematic framework of five categories of stakeholders (i.e., genome-driven stakeholders, industry-driven stakeholders, history-driven stakeholders, value-driven stakeholders, and social justice-driven stakeholders) that shape the public's discourse. Moving beyond the dialectical ethics that have governed the public discourse, we also identify the normative values and interests that motivate different stakeholders' attitudes and decision-making through theoretical sampling under the grounded theory. We investigate the competing and conflicting values within the same category of stakeholders. For example, despite being industry-driven stakeholders, medical professionals' attitudes are driven by concerns about standards of care; in contrast, health insurance companies' concerns are centered on profit. We further explore the tensions between these stakeholders that impact their strategic alliances and pose challenges to the practices of direct-to-consumer genetic testing. Finally, we examine how these stakeholders and their corresponding values may shape future development and policies of direct-to-consumer genetic testing in the context of reproductive health.

Effect of TCF7L2 on the relationship between lifestyle factors and glycemic parameters: a systematic review

Background

Among candidate genes related to type 2 diabetes (T2DM), one of the strongest genes is Transcription factor 7 like 2 (TCF7L2), regarding the Genome-Wide Association Studies. We aimed to conduct a systematic review of the literature on the modification effect of TCF7L2 on the relation between glycemic parameters and lifestyle factors.

Methods

A systematic literature search was done for relevant publications using electronic databases, including PubMed, EMBASE, Scopus, and Web of Science, from January 1, 2000, to November 2, 2021.

Results

Thirty-eight studies (16 observational studies, six meal test trials, and 16 randomized controlled trials (RCTs)) were included. Most observational studies had been conducted on participants with non-diabetes showing that TCF7L2 modified the association between diet (fatty acids and fiber) and insulin resistance. In addition, findings from meal test trials showed that, compared to non-risk-allele carriers, consumption of meals with different percentages of total dietary fat in healthy risk-allele carriers increased glucose concentrations and impaired insulin sensitivity. However, ten RCTs, with intervention periods of less than ten weeks and more than one year, showed that TCF7L2 did not modify glycemic parameters in response to a dietary intervention involving different macronutrients. However, two weight loss dietary RCTs with more than 1-year duration showed that serum glucose and insulin levels decreased and insulin resistance improved in non-risk allele subjects with overweight/obesity. Regarding artichoke extract supplementation (ALE), two RCTs observed that ALE supplementation significantly decreased insulin concentration and improved insulin resistance in the TT genotype of the rs7903146 variant of TCF7L2. In addition, four studies suggested that physical activity levels and smoking status modified the association between TCF7L2 and glycemic parameters. However, three studies observed no effect of TCF7L2 on glycemic parameters in participants with different levels of physical activity and smoking status.

Conclusion

The modification effects of TCF7L2 on the relation between the lifestyle factors (diet, physical activity, and smoking status) and glycemic parameters were contradictory.

PROSPERO registration number

CRD42020196327

Supplementary Information

The online version contains supplementary material available at 10.1186/s12937-022-00813-w.

Prevalence and clinical correlates of impaired glucose tolerance in first-episode versus chronic patients with schizophrenia

AIM

Studies using oral glucose tolerance tests (OGTT) have shown that impaired glucose metabolism presents in the early stages of schizophrenia (SCZ). However, there is a lack of studies on changes in glucose metabolism with the stage of the disease. We first explored the features of glucose metabolic pattern at different phases of male SCZ.

METHODS

We recruited 83 male first episode drug-naïve patients with SCZ (FEDN-SCZ) and 64 male chronic patients with SCZ (CH-SCZ), as well as 14 male healthy controls. The Positive and Negative Syndrome Scale (PANSS) was used to assess the psychopathology of patients. OGTT, fasting plasma glucose and lipid profiles of all participants were examined.

RESULTS

While the impaired glucose tolerance (IGT) rate of male SCZ patients was higher than that of HC (P < .05), there was no difference in IGT prevalence between FEDN-SCZ and CH-SCZ. In male FEDN-SCZ, LDL (OR = 2.64, 95% CI = 1.11-6.29, P = .028) and PANSS total score (OR = 1.03, 95% CI = 1.00-1.06, P = .046) were positively correlated with IGT; in male CH-SCZ, BMI (OR = 1.7, 95% CI = 1.08-2.67, P = .023), PANSS total score (OR = 0.82, 95% CI = 0.70-0.96, P = .015) and positive symptoms (OR = 0.45, 95% CI = 0.20-0.99, P = .046) were significantly correlated with IGT.

CONCLUSIONS

Our findings reflect different glucose metabolism patterns in different stages of SCZ.

Quantile-Dependent Heritability of Glucose, Insulin, Proinsulin, Insulin Resistance, and Glycated Hemoglobin

BACKGROUND

"Quantile-dependent expressivity" is a dependence of genetic effects on whether the phenotype (e.g., insulin resistance) is high or low relative to its distribution.

METHODS

Quantile-specific offspring-parent regression slopes (βOP) were estimated by quantile regression for fasting glucose concentrations in 6,453 offspring-parent pairs from the Framingham Heart Study.

RESULTS

Quantile-specific heritability (h2), estimated by 2βOP/(1 + rspouse), increased 0.0045 ± 0.0007 (p = 8.8 × 10-14) for each 1% increment in the fasting glucose distribution, that is, h2 ± SE were 0.057 ± 0.021, 0.095 ± 0.024, 0.146 ± 0.019, 0.293 ± 0.038, and 0.456 ± 0.061 at the 10th, 25th, 50th, 75th, and 90th percentiles of the fasting glucose distribution, respectively. Significant increases in quantile-specific heritability were also suggested for fasting insulin (p = 1.2 × 10-6), homeostatic model assessment of insulin resistance (HOMA-IR, p = 5.3 × 10-5), insulin/glucose ratio (p = 3.9 × 10-5), proinsulin (p = 1.4 × 10-6), proinsulin/insulin ratio (p = 2.7 × 10-5), and glucose concentrations during a glucose tolerance test (p = 0.001), and their logarithmically transformed values.

DISCUSSION/CONCLUSION

These findings suggest alternative interpretations to precision medicine and gene-environment interactions, including alternative interpretation of reported synergisms between ACE, ADRB3, PPAR-γ2, and TNF-α polymorphisms and being born small for gestational age on adult insulin resistance (fetal origin theory), and gene-adiposity (APOE, ENPP1, GCKR, IGF2BP2, IL-6, IRS-1, KIAA0280, LEPR, MFHAS1, RETN, TCF7L2), gene-exercise (INS), gene-diet (ACSL1, ELOVL6, IRS-1, PLIN, S100A9), and gene-socioeconomic interactions.

Disease Ionomics: Understanding the Role of Ions in Complex Disease

Ionomics is a novel multidisciplinary field that uses advanced techniques to investigate the composition and distribution of all minerals and trace elements in a living organism and their variations under diverse physiological and pathological conditions. It involves both high-throughput elemental profiling technologies and bioinformatic methods, providing opportunities to study the molecular mechanism underlying the metabolism, homeostasis, and cross-talk of these elements. While much effort has been made in exploring the ionomic traits relating to plant physiology and nutrition, the use of ionomics in the research of serious diseases is still in progress. In recent years, a number of ionomic studies have been carried out for a variety of complex diseases, which offer theoretical and practical insights into the etiology, early diagnosis, prognosis, and therapy of them. This review aims to give an overview of recent applications of ionomics in the study of complex diseases and discuss the latest advances and future trends in this area. Overall, disease ionomics may provide substantial information for systematic understanding of the properties of the elements and the dynamic network of elements involved in the onset and development of diseases.

Gene-lifestyle interaction on risk of type 2 diabetes: A systematic review

The pathophysiological influence of gene-lifestyle interactions on the risk to develop type 2 diabetes (T2D) is currently under intensive research. This systematic review summarizes the evidence for gene-lifestyle interactions regarding T2D incidence. MEDLINE, EMBASE, and Web of Science were systematically searched until 31 January 2019 to identify publication with (a) prospective study design; (b) T2D incidence; (c) gene-diet, gene-physical activity, and gene-weight loss intervention interaction; and (d) population who are healthy or prediabetic. Of 66 eligible publications, 28 reported significant interactions. A variety of different genetic variants and dietary factors were studied. Variants at TCF7L2 were most frequently investigated and showed interactions with fiber and whole grain on T2D incidence. Further gene-diet interactions were reported for, eg, a western dietary pattern with a T2D-GRS, fat and carbohydrate with IRS1 rs2943641, and heme iron with variants of HFE. Physical activity showed interaction with HNF1B, IRS1, PPARγ, ADRA2B, SLC2A2, and ABCC8 variants and weight loss interventions with ENPP1, PPARγ, ADIPOR2, ADRA2B, TNFα, and LIPC variants. However, most findings represent single study findings obtained in European ethnicities. Although some interactions have been reported, their conclusiveness is still low, as most findings were not yet replicated across multiple study populations.

Systems Biology of Selenium and Complex Disease

Selenium is an essential trace element for maintenance of overall health, whose deficiency and dyshomeostasis have been linked to a variety of diseases and disorders. The majority of previous researches focused on characterization of genes encoding selenoproteins or proteins involved in selenium metabolism as well as their functions. Many studies in humans also investigated the relationship between selenium and complex diseases, but their results have been inconsistent. In recent years, systems biology and "-omics" approaches have been widely used to study complex and global variations of selenium metabolism and function in physiological and different pathological conditions. The present paper reviews recent progress in large-scale and systematic analyses of the relationship between selenium status or selenoproteins and several complex diseases, mainly including population-based cohort studies and meta-analyses, genetic association studies, and some other omics-based studies. Advances in ionomics and its application in studying the interaction between selenium and other trace elements in human health and diseases are also discussed.

Genome-Wide Gene-Environment Interaction Analysis Using Set-Based Association Tests

The identification of gene-environment interactions (G × E) may eventually guide health-related choices and medical interventions for complex diseases. More powerful methods must be developed to identify G × E. The “adaptive combination of Bayes factors method” (ADABF) has been proposed as a powerful genome-wide polygenic approach to detect G × E. In this work, we evaluate its performance when serving as a gene-based G × E test. We compare ADABF with six tests including the “Set-Based gene-EnviRonment InterAction test” (SBERIA), “gene-environment set association test” (GESAT), etc. With extensive simulations, SBERIA and ADABF are found to be more powerful than other G × E tests. However, SBERIA suffers from a power loss when 50% SNP main effects are in the same direction with the SNP × E interaction effects while 50% are in the opposite direction. We further applied these seven G × E methods to the Taiwan Biobank data to explore gene× alcohol interactions on blood pressure levels. The ADAMTS7P1 gene at chromosome 15q25.2 was detected to interact with alcohol consumption on diastolic blood pressure (p = 9.5 × 10⁻⁷, according to the GESAT test). At this gene, the P-values provided by other six tests all reached the suggestive significance level (p < 5 × 10⁻⁵). Regarding the computation time required for a genome-wide G × E analysis, SBERIA is the fastest method, followed by ADABF. Considering the validity, power performance, robustness, and computation time, ADABF is recommended for genome-wide G × E analyses.

Gene Lifestyle Interactions With Relation to Obesity, Cardiometabolic, and Cardiovascular Traits Among South Asians

The rapid rise of obesity, type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD) during the last few decades among South Asians has been largely attributed to a major shift in lifestyles including physical inactivity, unhealthy dietary patterns, and an overall pattern of sedentary lifestyle. Genetic predisposition to these cardiometabolic risk factors may have interacted with these obesogenic environments in determining the higher cardiometabolic disease prevalence. Based on the premise that gene-environment interactions cause obesity and cardiometabolic diseases, we systematically searched the literature and considered the knowledge gaps that future studies might fulfill. We identified only seven published studies that focused specifically on gene-environment interactions for cardiometabolic traits in South Asians, most of which were limited by relatively small sample and lack of replication. Some studies reported that the differences in metabolic response to higher physical activity and low caloric diet might be modified by genetic risk related to these cardiometabolic traits. Although studies on gene lifestyle interactions in cardiometabolic traits report significant interactions, future studies must focus on more precise assessment of lifestyle factors, investigation of a larger set of genetic variants and the application of powerful statistical methods to facilitate translatable approaches. Future studies should also be integrated with findings both using mechanistic studies through laboratory settings and randomized clinical trials for clinical outcomes.

Adiposity and Genetic Factors in Relation to Triglycerides and Triglyceride-Rich Lipoproteins in the Women's Genome Health Study

BACKGROUND

Previous results from Scandinavian cohorts have shown that obesity accentuates the effects of common genetic susceptibility variants on increased triglycerides (TG). Whether such interactions are present in the US population and further selective for particular TG-rich lipoprotein subfractions is unknown.

METHODS

We examined these questions using body mass index (BMI) and waist circumference (WC) among women of European ancestry from the Women's Genome Health Study (WGHS) (n = 21840 for BMI; n = 19313 for WC). A weighted genetic risk score (TG-wGRS) based on 40 published TG-associated single-nucleotide polymorphisms was calculated using published effect estimates.

RESULTS

Comparing overweight (BMI ≥ 25 kg/m²) and normal weight (BMI < 25 kg/m²) WGHS women, each unit increase of TG-wGRS was associated with TG increases of 1.013% and 1.011%, respectively, and this differential association was significant (P_interaction = 0.014). Metaanalyses combining results for WGHS BMI with the 4 Scandinavian cohorts (INTER99, HEALTH2006, GLACIER, MDC) (total n = 40026) yielded a more significant interaction (P_interaction = 0.001). Similarly, we observed differential association of the TG-wGRS with TG (P_interaction = 0.006) in strata of WC (<80 cm vs ≥80 cm). Metaanalysis with 2 additional cohorts reporting WC (INTER99 and HEALTH2006) (total n = 27834) was significant with consistent effects (P_interaction = 0.006). We also observed highly significant interactions of the TG-wGRS across the strata of BMI with very large, medium, and small TG-rich lipoprotein subfractions measured by nuclear magnetic resonance spectroscopy (all P_interactions < 0.0001). The differential effects were strongest for very large TG-rich lipoprotein.

CONCLUSIONS

Our results support the original findings and suggest that obese individuals may be more susceptible to aggregated genetic risk associated with common TG-raising alleles, with effects accentuated in the large TG-rich lipoprotein subfraction.

TCF21 and the environmental sensor aryl-hydrocarbon receptor cooperate to activate a pro-inflammatory gene expression program in coronary artery smooth muscle cells

Both environmental factors and genetic loci have been associated with coronary artery disease (CAD), however gene-gene and gene-environment interactions that might identify molecular mechanisms of risk are not easily studied by human genetic approaches. We have previously identified the transcription factor TCF21 as the causal CAD gene at 6q23.2 and characterized its downstream transcriptional network that is enriched for CAD GWAS genes. Here we investigate the hypothesis that TCF21 interacts with a downstream target gene, the aryl hydrocarbon receptor (AHR), a ligand-activated transcription factor that mediates the cellular response to environmental contaminants, including dioxin and polycyclic aromatic hydrocarbons (e.g., tobacco smoke). Perturbation of TCF21 expression in human coronary artery smooth muscle cells (HCASMC) revealed that TCF21 promotes expression of AHR, its heterodimerization partner ARNT, and cooperates with these factors to upregulate a number of inflammatory downstream disease related genes including IL1A, MMP1, and CYP1A1. TCF21 was shown to bind in AHR, ARNT and downstream target gene loci, and co-localization was noted for AHR-ARNT and TCF21 binding sites genome-wide in regions of HCASMC open chromatin. These regions of co-localization were found to be enriched for GWAS signals associated with cardio-metabolic as well as chronic inflammatory disease phenotypes. Finally, we show that similar to TCF21, AHR gene expression is increased in atherosclerotic lesions in mice in vivo using laser capture microdissection, and AHR protein is localized in human carotid atherosclerotic lesions where it is associated with protein kinases with a critical role in innate immune response. These data suggest that TCF21 can cooperate with AHR to activate an inflammatory gene expression program that is exacerbated by environmental stimuli, and may contribute to the overall risk for CAD.

Gene-Diet Interaction and Precision Nutrition in Obesity

The rapid rise of obesity during the past decades has coincided with a profound shift of our living environment, including unhealthy dietary patterns, a sedentary lifestyle, and physical inactivity. Genetic predisposition to obesity may have interacted with such an obesogenic environment in determining the obesity epidemic. Growing studies have found that changes in adiposity and metabolic response to low-calorie weight loss diets might be modified by genetic variants related to obesity, metabolic status and preference to nutrients. This review summarized data from recent studies of gene-diet interactions, and discussed integration of research of metabolomics and gut microbiome, as well as potential application of the findings in precision nutrition.

Gene-obesogenic environment interactions in the UK Biobank study

Background

Previous studies have suggested that modern obesogenic environments accentuate the genetic risk of obesity. However, these studies have proven controversial as to which, if any, measures of the environment accentuate genetic susceptibility to high body mass index (BMI).

Methods

We used up to 120 000 adults from the UK Biobank study to test the hypothesis that high-risk obesogenic environments and behaviours accentuate genetic susceptibility to obesity. We used BMI as the outcome and a 69-variant genetic risk score (GRS) for obesity and 12 measures of the obesogenic environment as exposures. These measures included Townsend deprivation index (TDI) as a measure of socio-economic position, TV watching, a 'Westernized' diet and physical activity. We performed several negative control tests, including randomly selecting groups of different average BMIs, using a simulated environment and including sun-protection use as an environment.

Results

We found gene-environment interactions with TDI (Pinteraction = 3 × 10 -10 ), self-reported TV watching (Pinteraction = 7 × 10 -5 ) and self-reported physical activity (Pinteraction = 5 × 10 -6 ). Within the group of 50% living in the most relatively deprived situations, carrying 10 additional BMI-raising alleles was associated with approximately 3.8 kg extra weight in someone 1.73 m tall. In contrast, within the group of 50% living in the least deprivation, carrying 10 additional BMI-raising alleles was associated with approximately 2.9 kg extra weight. The interactions were weaker, but present, with the negative controls, including sun-protection use, indicating that residual confounding is likely.

Conclusions

Our findings suggest that the obesogenic environment accentuates the risk of obesity in genetically susceptible adults. Of the factors we tested, relative social deprivation best captures the aspects of the obesogenic environment responsible.

Impaired glucose tolerance in first-episode drug-naïve patients with schizophrenia: relationships with clinical phenotypes and cognitive deficits

BACKGROUND

Schizophrenia patients have a higher prevalence of type 2 diabetes mellitus with impaired glucose tolerance (IGT) than normals. We examined the relationship between IGT and clinical phenotypes or cognitive deficits in first-episode, drug-naïve (FEDN) Han Chinese patients with schizophrenia.

METHOD

A total of 175 in-patients were compared with 31 healthy controls on anthropometric measures and fasting plasma levels of glucose, insulin and lipids. They were also compared using a 75 g oral glucose tolerance test and the homeostasis model assessment of insulin resistance (HOMA-IR). Neurocognitive functioning was assessed using the MATRICS Consensus Cognitive Battery (MCCB). Patient psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS).

RESULTS

Of the patients, 24.5% had IGT compared with none of the controls, and they also had significantly higher levels of fasting blood glucose and 2-h glucose after an oral glucose load, and were more insulin resistant. Compared with those patients with normal glucose tolerance, the IGT patients were older, had a later age of onset, higher waist or hip circumference and body mass index, higher levels of low-density lipoprotein and triglycerides and higher insulin resistance. Furthermore, IGT patients had higher PANSS total and negative symptom subscale scores, but no greater cognitive impairment except on the emotional intelligence index of the MCCB.

CONCLUSIONS

IGT occurs with greater frequency in FEDN schizophrenia, and shows association with demographic and anthropometric parameters, as well as with clinical symptoms but minimally with cognitive impairment during the early course of the disorder.