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.1

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

Sugar-sweetened beverage consumption and genetic predisposition to obesity in 2 Swedish cohorts.

BACKGROUND: The consumption of sugar-sweetened beverages (SSBs), which has increased substantially during the last decades, has been associated with obesity and weight gain. OBJECTIVE: Common genetic susceptibility to obesity has been shown to modify the association between SSB intake and obesity risk in 3 prospective cohorts from the United States. We aimed to replicate these findings in 2 large Swedish cohorts. DESIGN: Data were available for 21,824 healthy participants from the Malmö Diet and Cancer study and 4902 healthy participants from the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk Study. Self-reported SSB intake was categorized into 4 levels (seldom, low, medium, and high). Unweighted and weighted genetic risk scores (GRSs) were constructed based on 30 body mass index [(BMI) in kg/m(2)]-associated loci, and effect modification was assessed in linear regression equations by modeling the product and marginal effects of the GRS and SSB intake adjusted for age-, sex-, and cohort-specific covariates, with BMI as the outcome. In a secondary analysis, models were additionally adjusted for putative confounders (total energy intake, alcohol consumption, smoking status, and physical activity). RESULTS: In an inverse variance-weighted fixed-effects meta-analysis, each SSB intake category increment was associated with a 0.18 higher BMI (SE = 0.02; P = 1.7 × 10(-20); n = 26,726). In the fully adjusted model, a nominal significant interaction between SSB intake category and the unweighted GRS was observed (P-interaction = 0.03). Comparing the participants within the top and bottom quartiles of the GRS to each increment in SSB intake was associated with 0.24 (SE = 0.04; P = 2.9 × 10(-8); n = 6766) and 0.15 (SE = 0.04; P = 1.3 × 10(-4); n = 6835) higher BMIs, respectively. CONCLUSIONS: The interaction observed in the Swedish cohorts is similar in magnitude to the previous analysis in US cohorts and indicates that the relation of SSB intake and BMI is stronger in people genetically predisposed to obesity

Migraine, inflammatory bowel disease and celiac disease: A Mendelian randomization study

Objective: To assess whether migraine may be genetically and/or causally associated with inflammatory bowel disease (IBD) or celiac disease. Background: Migraine has been linked to IBD and celiac disease in observational studies, but whether this link may be explained by a shared genetic basis or could be causal has not been established. The presence of a causal association could be clinically relevant, as treating one of these medical conditions might mitigate the symptoms of a causally linked condition. Methods: Linkage disequilibrium score regression and two-sample bidirectional Mendelian randomization analyses were performed using summary statistics from cohort-based genome-wide association studies of migraine (59,674 cases; 316,078 controls), IBD (25,042 cases; 34,915 controls) and celiac disease (11,812 or 4533 cases; 11,837 or 10,750 controls). Migraine with and without aura were analyzed separately, as were the two IBD subtypes Crohn's disease and ulcerative colitis. Positive control analyses and conventional Mendelian randomization sensitivity analyses were performed. Results: Migraine was not genetically correlated with IBD or celiac disease. No evidence was observed for IBD (odds ratio [OR] 1.00, 95% confidence interval [CI] 0.99-1.02, p = 0.703) or celiac disease (OR 1.00, 95% CI 0.99-1.02, p = 0.912) causing migraine or migraine causing either IBD (OR 1.08, 95% CI 0.96-1.22, p = 0.181) or celiac disease (OR 1.08, 95% CI 0.79-1.48, p = 0.614) when all participants with migraine were analyzed jointly. There was some indication of a causal association between celiac disease and migraine with aura (OR 1.04, 95% CI 1.00-1.08, p = 0.045), between celiac disease and migraine without aura (OR 0.95, 95% CI 0.92-0.99, p = 0.006), as well as between migraine without aura and ulcerative colitis (OR 1.15, 95% CI 1.02-1.29, p = 0.025). However, the results were not significant after multiple testing correction. Conclusions: We found no evidence of a shared genetic basis or of a causal association between migraine and either IBD or celiac disease, although we obtained some indications of causal associations with migraine subtypes. Keywords: Mendelian randomization; celiac disease; gastrointestinal disease; genetic correlation; inflammatory bowel disease; migraine

Exploring sex differences: insights into gene expression, neuroanatomy, neurochemistry, cognition, and pathology

Increased knowledge about sex differences is important for development of individualized treatments against many diseases as well as understanding behavioral and pathological differences. This review summarizes sex chromosome effects on gene expression, epigenetics, and hormones in relation to the brain. We explore neuroanatomy, neurochemistry, cognition, and brain pathology aiming to explain the current state of the art. While some domains exhibit strong differences, others reveal subtle differences whose overall significance warrants clarification. We hope that the current review increases awareness and serves as a basis for the planning of future studies that consider both sexes equally regarding similarities and differences

Association of lipid-related genetic variants with the incidence of atrial fibrillation: The AFGen consortium

Background: Several studies have shown associations between blood lipid levels and the risk of atrial fibrillation (AF). To test the potential effect of blood lipids with AF risk, we assessed whether previously developed lipid gene scores, used as instrumental variables, are associated with the incidence of AF in 7 large cohorts. Methods: We analyzed 64,901 individuals of European ancestry without previous AF at baseline and with lipid gene scores. Lipid-specific gene scores, based on loci significantly associated with lipid levels, were calculated. Additionally, non-pleiotropic gene scores for high-density lipoprotein cholesterol (HDLc) and low-density lipoprotein cholesterol (LDLc) were calculated using SNPs that were only associated with the specific lipid fraction. Cox models were used to estimate the hazard ratio (HR) and 95% confidence intervals (CI) of AF per 1-standard deviation (SD) increase of each lipid gene score. Results: During a mean follow-up of 12.0 years, 5434 (8.4%) incident AF cases were identified. After meta-analysis, the HDLc, LDLc, total cholesterol, and triglyceride gene scores were not associated with incidence of AF. Multivariable-adjusted HR (95% CI) were 1.01 (0.98-1.03); 0.98 (0.96-1.01); 0.98 (0.95-1.02); 0.99 (0.97-1.02), respectively. Similarly, non-pleiotropic HDLc and LDLc gene scores showed no association with incident AF: HR (95% CI) = 1.00 (0.97-1.03); 1.01 (0.99-1.04). Conclusions In this large cohort study of individuals of European ancestry, gene scores for lipid fractions were not associated with incident AF

Using genetics to test the causal relationship of total adiposity and periodontitis: Mendelian randomization analyses in the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium

Background: The observational relationship between obesity and periodontitis is widely known, yet causal evidence is lacking. Our objective was to investigate causal associations between periodontitis and body mass index (BMI).Methods: We performed Mendelian randomization analyses with BMI-associated loci combined in a genetic risk score (GRS) as the instrument for BMI. All analyses were conducted within the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium in 13 studies from Europe and the USA, including 49 066 participants with clinically assessed (seven studies, 42.1% of participants) and self-reported (six studies, 57.9% of participants) periodontitis and genotype data (17 672/31 394 with/without periodontitis); 68 761 participants with BMI and genotype data; and 57 871 participants (18 881/38 990 with/without periodontitis) with data on BMI and periodontitis.Results: In the observational meta-analysis of all participants, the pooled crude observational odds ratio (OR) for periodontitis was 1.13 [95% confidence interval (CI): 1.03, 1.24] per standard deviation increase of BMI. Controlling for potential confounders attenuated this estimate (OR = 1.08; 95% CI:1.03, 1.12). For clinically assessed periodontitis, corresponding ORs were 1.25 (95% CI: 1.10, 1.42) and 1.13 (95% CI: 1.10, 1.17), respectively. In the genetic association meta-analysis, the OR for periodontitis was 1.01 (95% CI: 0.99, 1.03) per GRS unit (per one effect allele) in all participants and 1.00 (95% CI: 0.97, 1.03) in participants with clinically assessed periodontitis. The instrumental variable meta-analysis of all participants yielded an OR of 1.05 (95% CI: 0.80, 1.38) per BMI standard deviation, and 0.90 (95% CI: 0.56, 1.46) in participants with clinical data.Conclusions: Our study does not support total adiposity as a causal risk factor for periodontitis, as the point estimate is very close to the null in the causal inference analysis, with wide confidence intervals

Gene × Physical Activity Interactions in Obesity: Combined Analysis of 111,421 Individuals of European Ancestry

Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age2, sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, Pinteraction = 0.014 vs. n = 71,611, Pinteraction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (Pinteraction = 0.003) and the SEC16B rs10913469 (Pinteraction = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal