Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Neurobiological Mechanisms of Nicotine Reward and Aversion

Neuronal nicotinic acetylcholine receptors (nAChRs) regulate the rewarding actions of nicotine contained in tobacco that establish and maintain the smoking habit. nAChRs also regulate the aversive properties of nicotine, sensitivity to which decreases tobacco use and protects against tobacco use disorder. These opposing behavioral actions of nicotine reflect nAChR expression in brain reward and aversion circuits. nAChRs containing α4 and β2 subunits are responsible for the high-affinity nicotine binding sites in the brain and are densely expressed by reward-relevant neurons, most notably dopaminergic, GABAergic, and glutamatergic neurons in the ventral tegmental area. High-affinity nAChRs can incorporate additional subunits, including β3, α6, or α5 subunits, with the resulting nAChR subtypes playing discrete and dissociable roles in the stimulatory actions of nicotine on brain dopamine transmission. nAChRs in brain dopamine circuits also participate in aversive reactions to nicotine and the negative affective state experienced during nicotine withdrawal. nAChRs containing α3 and β4 subunits are responsible for the low-affinity nicotine binding sites in the brain and are enriched in brain sites involved in aversion, including the medial habenula, interpeduncular nucleus, and nucleus of the solitary tract, brain sites in which α5 nAChR subunits are also expressed. These aversion-related brain sites regulate nicotine avoidance behaviors, and genetic variation that modifies the function of nAChRs in these sites increases vulnerability to tobacco dependence and smoking-related diseases. Here, we review the molecular, cellular, and circuit-level mechanisms through which nicotine elicits reward and aversion and the adaptations in these processes that drive the development of nicotine dependence. SIGNIFICANCE STATEMENT: Tobacco use disorder in the form of habitual cigarette smoking or regular use of other tobacco-related products is a major cause of death and disease worldwide. This article reviews the actions of nicotine in the brain that contribute to tobacco use disorder.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

Effect of dietary fat intake and genetic risk on glucose and insulin-related traits in Brazilian young adults

PURPOSE

The development of metabolic diseases such as type 2 diabetes (T2D) is closely linked to a complex interplay between genetic and dietary factors. The prevalence of abdominal obesity, hyperinsulinemia, dyslipidaemia, and high blood pressure among Brazilian adolescents is increasing and hence, early lifestyle interventions targeting these factors might be an effective strategy to prevent or slow the progression of T2D.

METHODS

We aimed to assess the interaction between dietary and genetic factors on metabolic disease-related traits in 200 healthy Brazilian young adults. Dietary intake was assessed using 3-day food records. Ten metabolic disease-related single nucleotide polymorphisms (SNPs) were used to construct a metabolic-genetic risk score (metabolic-GRS).

RESULTS

We found significant interactions between the metabolic-GRS and total fat intake on fasting insulin level (Pinteraction = 0.017), insulin-glucose ratio (Pinteraction = 0.010) and HOMA-B (Pinteraction = 0.002), respectively, in addition to a borderline GRS-fat intake interaction on HOMA-IR (Pinteraction = 0.051). Within the high-fat intake category [37.98 ± 3.39% of total energy intake (TEI)], individuals with ≥ 5 risk alleles had increased fasting insulin level (P = 0.021), insulin-glucose ratio (P = 0.010), HOMA-B (P = 0.001) and HOMA-IR (P = 0.053) than those with < 5 risk alleles.

CONCLUSION

Our study has demonstrated a novel GRS-fat intake interaction in young Brazilian adults, where individuals with higher genetic risk and fat intake had increased glucose and insulin-related traits than those with lower genetic risk. Large intervention and follow-up studies with an objective assessment of dietary factors are needed to confirm our findings.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40200-021-00863-7.

Histone H4 lysine 16 acetylation controls central carbon metabolism and diet-induced obesity in mice

Noncommunicable diseases (NCDs) account for over 70% of deaths world-wide. Previous work has linked NCDs such as type 2 diabetes (T2D) to disruption of chromatin regulators. However, the exact molecular origins of these chronic conditions remain elusive. Here, we identify the H4 lysine 16 acetyltransferase MOF as a critical regulator of central carbon metabolism. High-throughput metabolomics unveil a systemic amino acid and carbohydrate imbalance in Mof deficient mice, manifesting in T2D predisposition. Oral glucose tolerance testing (OGTT) reveals defects in glucose assimilation and insulin secretion in these animals. Furthermore, Mof deficient mice are resistant to diet-induced fat gain due to defects in glucose uptake in adipose tissue. MOF-mediated H4K16ac deposition controls expression of the master regulator of glucose metabolism, Pparg and the entire downstream transcriptional network. Glucose uptake and lipid storage can be reconstituted in MOF-depleted adipocytes in vitro by ectopic Glut4 expression, PPARγ agonist thiazolidinedione (TZD) treatment or SIRT1 inhibition. Hence, chronic imbalance in H4K16ac promotes a destabilisation of metabolism triggering the development of a metabolic disorder, and its maintenance provides an unprecedented regulatory epigenetic mechanism controlling diet-induced obesity.

Non-linear interaction between physical activity and polygenic risk score of body mass index in Danish and Russian populations

Body mass index (BMI) is a highly heritable polygenic trait. It is also affected by various environmental and behavioral risk factors. We used a BMI polygenic risk score (PRS) to study the interplay between the genetic and environmental factors defining BMI. First, we generated a BMI PRS that explained more variance than a BMI genetic risk score (GRS), which was using only genome-wide significant BMI-associated variants (R² = 13.1% compared to 6.1%). Second, we analyzed interactions between BMI PRS and seven environmental factors. We found a significant interaction between physical activity and BMI PRS, even when the well-known effect of the FTO region was excluded from the PRS, using a small dataset of 6,179 samples. Third, we stratified the study population into two risk groups using BMI PRS. The top 22% of the studied populations were included in a high PRS risk group. Engagement in self-reported physical activity was associated with a 1.66 kg/m² decrease in BMI in this group, compared to a 0.84 kg/m² decrease in BMI in the rest of the population. Our results (i) confirm that genetic background strongly affects adult BMI in the general population, (ii) show a non-linear interaction between BMI genetics and physical activity, and (iii) provide a standardized framework for future gene-environment interaction analyses.

Using Summary Statistics to Model Multiplicative Combinations of Initially Analyzed Phenotypes With a Flexible Choice of Covariates

While the promise of electronic medical record and biobank data is large, major questions remain about patient privacy, computational hurdles, and data access. One promising area of recent development is pre-computing non-individually identifiable summary statistics to be made publicly available for exploration and downstream analysis. In this manuscript we demonstrate how to utilize pre-computed linear association statistics between individual genetic variants and phenotypes to infer genetic relationships between products of phenotypes (e.g., ratios; logical combinations of binary phenotypes using "and" and "or") with customized covariate choices. We propose a method to approximate covariate adjusted linear models for products and logical combinations of phenotypes using only pre-computed summary statistics. We evaluate our method's accuracy through several simulation studies and an application modeling ratios of fatty acids using data from the Framingham Heart Study. These studies show consistent ability to recapitulate analysis results performed on individual level data including maintenance of the Type I error rate, power, and effect size estimates. An implementation of this proposed method is available in the publicly available R package pcsstools.

Genome-wide methylation data improves dissection of the effect of smoking on body mass index

Variation in obesity-related traits has a genetic basis with heritabilities between 40 and 70%. While the global obesity pandemic is usually associated with environmental changes related to lifestyle and socioeconomic changes, most genetic studies do not include all relevant environmental covariates, so the genetic contribution to variation in obesity-related traits cannot be accurately assessed. Some studies have described interactions between a few individual genes linked to obesity and environmental variables but there is no agreement on their total contribution to differences between individuals. Here we compared self-reported smoking data and a methylation-based proxy to explore the effect of smoking and genome-by-smoking interactions on obesity related traits from a genome-wide perspective to estimate the amount of variance they explain. Our results indicate that exploiting omic measures can improve models for complex traits such as obesity and can be used as a substitute for, or jointly with, environmental records to better understand causes of disease.

Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations

Supplemental Digital Content is available in the text.

Background:

ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the CHREBP locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the CHREBP locus and dyslipidemia.

Methods:

Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near CHREBP were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake.

Results:

In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16–3.07] mg/dL per allele; P<0.0001), but not significantly among the lowest SSB consumers (P=0.81; P_Diff <0.0001). Similar results were observed for 2 additional variants (rs35709627 and rs71556736). For triglyceride, rs55673514 was positively associated with triglyceride concentrations only among the highest SSB consumers (β, 0.06 [95% CI, 0.02–0.09] ln-mg/dL per allele, P=0.001) but not the lowest SSB consumers (P=0.84; P_Diff=0.0005).

Conclusions:

Our results identified genetic variants in the CHREBP locus that may protect against SSB-associated reductions in HDL-C and other variants that may exacerbate SSB-associated increases in triglyceride concentrations.

Registration:

URL: https://www.clinicaltrials.gov; Unique identifier: NCT00005133, NCT00005121, NCT00005487, and NCT00000479.

Genome-wide association study in the Taiwan biobank identifies four novel genes for human height: NABP2, RASA2, RNF41 and SLC39A5

Numerous genome-wide association studies (GWASs) have been conducted for the identification of genetic variants involved with human height. The vast majority of these studies, however, have been conducted in populations of European ancestry. Here, we report the first GWAS of adult height in the Taiwan Biobank using a discovery sample of 14 571 individuals and an independent replication sample of 20 506 individuals. From our analysis we generalize to the Taiwanese population genome-wide significant associations with height and 18 previously identified genes in European and non-Taiwanese East Asian populations. We also identify and replicate, at the genome-wide significance level, associated variants for height in four novel genes at two loci that have not previously been reported: RASA2 on chromosome 3 and NABP2, RNF41, and SLC39A5 at 12q13.3 on chromosome 12. RASA2 and RNF41 are strong candidates for having a role in height with copy number and loss of function variants in RASA2 previously found to be associated with short stature disorders, and decreased expression of the RNF41 gene resulting in insulin resistance in skeletal muscle. The results from our analysis of the Taiwan Biobank underscore the potential for the identification of novel genetic discoveries in underrepresented worldwide populations, even for traits, such as height, that have been extensively investigated in large-scale studies of European ancestry populations.

Genome-wide association study of body fat distribution traits in Hispanics/Latinos from the HCHS/SOL

Central obesity is a leading health concern with a great burden carried by ethnic minority populations, especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aimed to identify the loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC) and hip circumference (HIP) adjusted for body mass index (adjBMI) by using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); determine if differences in associations differ by background group within HCHS/SOL and determine whether previously reported associations generalize to HCHS/SOL. Our analyses included 7472 women and 5200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban and Dominican) background residing in the USA. We performed genome-wide association analyses stratified and combined across sexes using linear mixed-model regression. We identified 16 variants for waist-to-hip ratio adjusted for body mass index (WHRadjBMI), 22 for waist circumference adjusted for body mass index (WCadjBMI) and 28 for hip circumference adjusted for body mass index (HIPadjBMI), which reached suggestive significance (P < 1 × 10-6). Many loci exhibited differences in strength of associations by ethnic background and sex. We brought a total of 66 variants forward for validation in cohorts (N = 34 161) with participants of Hispanic/Latino, African and European descent. We confirmed four novel loci (P < 0.05 and consistent direction of effect, and P < 5 × 10-8 after meta-analysis), including two for WHRadjBMI (rs13301996, rs79478137); one for WCadjBMI (rs3168072) and one for HIPadjBMI (rs28692724). Also, we generalized previously reported associations to HCHS/SOL, (8 for WHRadjBMI, 10 for WCadjBMI and 12 for HIPadjBMI). Our study highlights the importance of large-scale genomic studies in ancestrally diverse Hispanic/Latino populations for identifying and characterizing central obesity susceptibility that may be ancestry-specific.

Genetic Determinants of Peripheral Artery Disease

Peripheral artery disease-atherosclerosis of the abdominal aorta and lower extremity vascular bed-is a complex disease with both environmental and genetic determinants. Unmitigated disease is associated with major functional decline and can lead to chronic limb-threatening ischemia, amputation, and increased mortality. Over the last 10 years, major advances have been made in identifying the genetic basis of this common, complex disease. In this review, we provide an overview of the primary types of genetic analyses performed for peripheral artery disease, including heritability and linkage studies, and more recently biobank-based genome-wide association studies. Looking forward, we highlight areas of future study including efforts to identify causal peripheral artery disease genes, rare variant and structural variant analyses using whole-exome and whole-genome sequencing data, and the need to include individuals of diverse genetic ancestries.

Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments

Over a decade of genome-wide association studies (GWAS) have led to the finding of extreme polygenicity of complex traits. The phenomenon that "all genes affect every complex trait" complicates Mendelian Randomization (MR) studies, where natural genetic variations are used as instruments to infer the causal effect of heritable risk factors. We reexamine the assumptions of existing MR methods and show how they need to be clarified to allow for pervasive horizontal pleiotropy and heterogeneous effect sizes. We propose a comprehensive framework GRAPPLE to analyze the causal effect of target risk factors with heterogeneous genetic instruments and identify possible pleiotropic patterns from data. By using GWAS summary statistics, GRAPPLE can efficiently use both strong and weak genetic instruments, detect the existence of multiple pleiotropic pathways, determine the causal direction and perform multivariable MR to adjust for confounding risk factors. With GRAPPLE, we analyze the effect of blood lipids, body mass index, and systolic blood pressure on 25 disease outcomes, gaining new information on their causal relationships and potential pleiotropic pathways involved.

Associations of Genetic Factors, Educational Attainment, and Their Interaction With Kidney Function Outcomes

Both genetic predisposition and low educational attainment (EA) are associated with higher risk of chronic kidney disease. We examined the interaction of EA and genetic risk in kidney function outcomes. We included 3,597 participants from the Prevention of Renal and Vascular End-Stage Disease Cohort Study, a longitudinal study in a community-based sample from Groningen, the Netherlands (median follow-up, 11 years; 1997–2012). Kidney function was approximated by obtaining estimated glomerular filtration rate (eGFR) from serum creatinine and cystatin C. Individual longitudinal linear eGFR trajectories were derived from linear mixed models. Genotype data on 63 single-nucleotide polymorphisms, with known associations with eGFR, were used to calculate an allele-weighted genetic score (WGS). EA was categorized into high, medium, and low. In ordinary least squares analysis, higher WGS and lower EA showed additive effects on reduced baseline eGFR; the interaction term was nonsignificant. In analysis of eGFR decline, the significant interaction term suggested amplification of genetic risk by low EA. Adjustment for known renal risk factors did not affect our results. This study presents the first evidence of gene-environment interaction between EA and a WGS for eGFR decline and provides population-level insights into the mechanisms underlying socioeconomic disparities in chronic kidney disease.

Lifestyle Risk Score: handling missingness of individual lifestyle components in meta-analysis of gene-by-lifestyle interactions

Recent studies consider lifestyle risk score (LRS), an aggregation of multiple lifestyle exposures, in identifying association of gene-lifestyle interaction with disease traits. However, not all cohorts have data on all lifestyle factors, leading to increased heterogeneity in the environmental exposure in collaborative meta-analyses. We compared and evaluated four approaches (Naïve, Safe, Complete and Moderator Approaches) to handle the missingness in LRS-stratified meta-analyses under various scenarios. Compared to "benchmark" results with all lifestyle factors available for all cohorts, the Complete Approach, which included only cohorts with all lifestyle components, was underpowered due to lower sample size, and the Naïve Approach, which utilized all available data and ignored the missingness, was slightly inflated. The Safe Approach, which used all data in LRS-exposed group and only included cohorts with all lifestyle factors available in the LRS-unexposed group, and the Moderator Approach, which handled missingness via moderator meta-regression, were both slightly conservative and yielded almost identical p values. We also evaluated the performance of the Safe Approach under different scenarios. We observed that the larger the proportion of cohorts without missingness included, the more accurate the results compared to "benchmark" results. In conclusion, we generally recommend the Safe Approach, a straightforward and non-inflated approach, to handle heterogeneity among cohorts in the LRS based genome-wide interaction meta-analyses.

Neuropeptide Y gene variants in obesity, dietary intake, blood pressure, lipid and glucose metabolism: A longitudinal birth cohort study

OBJECTIVE

Neuropeptide Y affects several physiological functions, notably appetite regulation. We analysed the association between four single nucleotide polymorphisms (SNP) in the NPY gene (rs5574, rs16147, rs16139, rs17149106) and measures of obesity, dietary intake, physical activity, blood pressure, glucose and lipid metabolism from adolescence to young adulthood.

METHODS

The sample included both birth cohorts of the Estonian Children Personality Behaviour and Health Study at ages 15 (n = 1075 with available complete data), 18 (n = 913) and 25 (n = 926) years. Linear mixed-effects regression models were used for longitudinal association between NPY SNP-s and variables of interest. Associations at ages 15, 18 and 25 were analysed by ANOVA.

RESULTS

Rs5574 CC-homozygotes had a greater increase per year in waist-to-hip ratio (WHR) and a smaller decrease in daily energy intake and carbohydrate intake from age 15-25 years; fasting glucose and cholesterol were higher in rs5574 CC-homozygotes. Rs16147 TT-homozygotes had higher body weight and a greater increase in sum of 5 skinfolds, waist circumference, WHR and waist-to-height ratio; however, they had lower carbohydrate intake throughout the observation period. Rs16147 TT-homozygotes and both rs16139 and rs17149106 heterozygotes had higher triglyceride levels. All NPY SNP-s were associated with blood pressure: rs5574 TT-and rs16147 CC-homozygotes had a smaller increase in diastolic blood pressure, while rs16139 and rs17149106 heterozygous had lower blood pressure throughout the study.

CONCLUSION

Variants of the NPY gene were associated with measures of obesity, dietary intake, glucose and lipid metabolism and blood pressure from adolescence to young adulthood.

Evidence for shared genetics between physical activity, sedentary behaviour and adiposity-related traits

Observational, cross-sectional and longitudinal studies showed that physical activity and sedentary behaviour are associated with adiposity-related traits, apparently in a bidirectional manner. Physical activity is also suggested to suppress the genetic risk of adiposity. Since phenotypic associations with genetic variants are not subject to reverse causation or confounding, they may be used as tools to shed light on cause and effect in this complex interdependency. We review the evidence for shared genetics of physical activity and adiposity-related traits and for gene-by-physical activity interactions on adiposity-related traits in human studies. We outline limitations, challenges and opportunities in studying and understanding of these relationships. In summary, physical activity and sedentary behaviour are genetically correlated with body mass index and fat percentage but may not be correlated with lean body mass. Mendelian randomisation analyses show that physical activity and sedentary behaviour have bidirectional relationships with adiposity. Several studies suggest that physical activity suppresses genetic risk of adiposity. No studies have yet tested whether adiposity enhances genetic predisposition to sedentariness. The complexity of the comprehensive causal model makes the assessment of the single or combined components challenging. Substantial progress in this field may need long-term intervention studies.

Birthweight DNA methylation signatures in infant saliva

Background

Low birthweight has been repeatedly associated with long-term adverse health outcomes and many non-communicable diseases. Our aim was to look-up cord blood birthweight-associated CpG sites identified by the PACE Consortium in infant saliva, and to explore saliva-specific DNA methylation signatures of birthweight.

Methods

DNA methylation was assessed using Infinium HumanMethylation450K array in 135 saliva samples collected from children of the NINFEA birth cohort at an average age of 10.8 (range 7–17) months. The association analyses between birthweight and DNA methylation variations were carried out using robust linear regression models both in the exploratory EWAS analyses and in the look-up of the PACE findings in infant saliva.

Results

None of the cord blood birthweight-associated CpGs identified by the PACE Consortium was associated with birthweight when analysed in infant saliva. In saliva EWAS analyses, considering a false discovery rate p-values < 0.05, birthweight as continuous variable was associated with DNA methylation in 44 CpG sites; being born small for gestational age (SGA, lower 10^th percentile of birthweight for gestational age according to WHO reference charts) was associated with DNA methylation in 44 CpGs, with only one overlapping CpG between the two analyses. Despite no overlap with PACE results at the CpG level, two of the top saliva birthweight CpGs mapped at genes associated with birthweight with the same direction of the effect also in the PACE Consortium (MACROD1 and RPTOR).

Conclusion

Our study provides an indication of the birthweight and SGA epigenetic salivary signatures in children around 10 months of age. DNA methylation signatures in cord blood may not be comparable with saliva DNA methylation signatures at about 10 months of age, suggesting that the birthweight epigenetic marks are likely time and tissue specific.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01053-1.

Differential Effect of Polymorphisms on Body Mass Index Across the Life Course of Japanese: The Japan Multi-Institutional Collaborative Cohort Study

BACKGROUND

Obesity is a reported risk factor for various health problems. Genome-wide association studies (GWASs) have identified numerous independent loci associated with body mass index (BMI). However, most of these have been focused on Europeans, and little evidence is available on the genetic effects across the life course of other ethnicities.

METHODS

We conducted a cross-sectional study to examine the associations of 282 GWAS-identified single nucleotide polymorphisms with three BMI-related traits, current BMI, BMI at 20 years old (BMI at 20), and change in BMI (BMI change), among 11,586 Japanese individuals enrolled in the Japan Multi-Institutional Collaborative Cohort study. Associations were examined using multivariable linear regression models.

RESULTS

We found a significant association (P < 0.05/282 = 1.77 × 10-4) between BMI and 11 polymorphisms in or near FTO, BDNF, TMEM18, HS6ST3, and BORCS7. The trend was similar between current BMI and BMI change, but differed from that of the BMI at 20. Among the significant variants, those on FTO were associated with all BMI traits, whereas those on TMEM18 and HS6SR3 were only associated with BMI at 20. The association of FTO loci with BMI remained, even after additional adjustment for dietary energy intake.

CONCLUSIONS

Previously reported BMI-associated loci discovered in Europeans were also identified in the Japanese population. Additionally, our results suggest that the effects of each loci on BMI may vary across the life course and that this variation may be caused by the differential effects of individual genes on BMI via different pathways.

Smoking and heart failure: a Mendelian randomization and mediation analysis

Aims

We performed a Mendelian randomization (MR) study to elucidate the associations of ever smoking, lifelong smoking duration, and smoking cessation with heart failure (HF) risk.

Methods and results

We extracted genetic variants associated with smoking initiation, age at initiation of regular smoking, cigarettes per day, and smoking cessation from the genome‐wide association study and Sequencing Consortium of Alcohol and Nicotine use (1.2 million individuals), as well as a composite lifetime smoking index from the UK Biobank (462 690 individuals). The associations between smoking phenotypes and HF were explored in the Heart Failure Molecular Epidemiology for Therapeutic Targets Consortium (47 309 cases; 930 014 controls) employing inverse variance‐weighted meta‐analysis and multivariable MR. The mediation effects of coronary artery disease and atrial fibrillation on smoking–HF risk were explored using mediation analysis. The odds ratios (ORs) for HF were 1.28 [95% confidence interval (CI), 1.22–1.36; P = 1.5 × 10⁻¹⁸] for ever regular smokers compared with never smokers and 1.25 (95% CI, 1.09–1.44; P = 1.6 × 10⁻³) for current smokers vs. former smokers. Genetic liability to smoking more cigarettes per day (OR, 1.37; 95% CI, 1.20–1.58; P = 6.4 × 10⁻⁶) and a higher composite lifetime smoking index (OR, 1.49; 95% CI, 1.31–1.70; P = 2.5 × 10⁻⁹) were associated with a higher risk of HF. The results were robust and consistent in all sensitivity analyses and multivariable MR after adjusting for HF risk factors, and their associations were independent of coronary artery disease and atrial fibrillation.

Conclusions

Genetic liability to ever smoking and a higher lifetime smoking burden are associated with a higher risk of HF.

Identification of genetic loci affecting body mass index through interaction with multiple environmental factors using structured linear mixed model

Multiple environmental factors could interact with a single genetic factor to affect disease phenotypes. We used Struct-LMM to identify genetic variants that interacted with environmental factors related to body mass index (BMI) using data from the Korea Association Resource. The following factors were investigated: alcohol consumption, education, physical activity metabolic equivalent of task (PAMET), income, total calorie intake, protein intake, carbohydrate intake, and smoking status. Initial analysis identified 7 potential single nucleotide polymorphisms (SNPs) that interacted with the environmental factors (P value < 5.00 × 10^-6). Of the 8 environmental factors, PAMET score was excluded for further analysis since it had an average Bayes Factor (BF) value < 1 (BF = 0.88). Interaction analysis using 7 environmental factors identified 11 SNPs (P value < 5.00 × 10^-6). Of these, rs2391331 had the most significant interaction (P value = 7.27 × 10^-9) and was located within the intron of EFNB2 (Chr 13). In addition, the gene-based genome-wide association study verified EFNB2 gene significantly interacting with 7 environmental factors (P value = 5.03 × 10^-10). BF analysis indicated that most environmental factors, except carbohydrate intake, contributed to the interaction of rs2391331 on BMI. Although the replication of the results in other cohorts is warranted, these findings proved the usefulness of Struct-LMM to identify the gene-environment interaction affecting disease.

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Association of Body Mass Index With Colorectal Cancer Risk by Genome-Wide Variants

BACKGROUND

Body mass index (BMI) is a complex phenotype that may interact with genetic variants to influence colorectal cancer risk.

METHODS

We tested multiplicative statistical interactions between BMI (per 5 kg/m2) and approximately 2.7 million single nucleotide polymorphisms with colorectal cancer risk among 14 059 colorectal cancer case (53.2% women) and 14 416 control (53.8% women) participants. All analyses were stratified by sex a priori. Statistical methods included 2-step (ie, Cocktail method) and single-step (ie, case-control logistic regression and a joint 2-degree of freedom test) procedures. All statistical tests were two-sided.

RESULTS

Each 5 kg/m2 increase in BMI was associated with higher risks of colorectal cancer, less so for women (odds ratio [OR] = 1.14, 95% confidence intervals [CI] = 1.11 to 1.18; P = 9.75 × 10-17) than for men (OR = 1.26, 95% CI = 1.20 to 1.32; P = 2.13 × 10-24). The 2-step Cocktail method identified an interaction for women, but not men, between BMI and a SMAD7 intronic variant at 18q21.1 (rs4939827; Pobserved = .0009; Pthreshold = .005). A joint 2-degree of freedom test was consistent with this finding for women (joint P = 2.43 × 10-10). Each 5 kg/m2 increase in BMI was more strongly associated with colorectal cancer risk for women with the rs4939827-CC genotype (OR = 1.24, 95% CI = 1.16 to 1.32; P = 2.60 × 10-10) than for women with the CT (OR = 1.14, 95% CI = 1.09 to 1.19; P = 1.04 × 10-8) or TT (OR = 1.07, 95% CI = 1.01 to 1.14; P = .02) genotypes.

CONCLUSION

These results provide novel insights on a potential mechanism through which a SMAD7 variant, previously identified as a susceptibility locus for colorectal cancer, and BMI may influence colorectal cancer risk for women.

BDNF Gene as a Precision Skill of Obesity Management

The scarcity of the results obtained for the treatment of obesity leads us to consider new strategies, contemplating all the factors involved in the development of the disease. One of the key molecules for controlling body weight and energy homeostasis is the brain-derived neurotrophic factor (BDNF). This work summarizes the mechanisms in which BDNF gene regulates this multifactorial disease. In addition, we discuss the role of other BDNF polymorphisms as genetic determinants of obesity. In this context, a total of 14 SNPs near or inside BDNF/BDNF-AS related to BMI were identified in various GWASs. Finally, we assess gene-diet interaction as a novel tool to prevent obesity and formulate solid and personalized nutritional management. Our research group has performed the first study on the association of BDNF-AS rs925946 polymorphism and calcium intake as potential modulators of the nutritional status. Although these results should be confirmed in future studies, they open the path for new prevention opportunities.

Parental lifespan and the likelihood of reaching the age of 90 years in the Netherlands Cohort Study

Aim

Growing evidence suggests an association between parental longevity and lifespan of subsequent generations. We aimed to reproduce earlier findings, showing a positive association between parental longevity and offspring's longevity. Additionally, we investigated whether this is mainly driven by the maternal or paternal germline in male and female offspring.

Methods

For these analyses, data from the oldest birth cohort (1916–17) of the Netherlands Cohort Study was used. Participants filled in a baseline questionnaire in 1986 (at age 68–70 years). Follow up for vital status information until the age of 90 years (2006–07) was >99.9% complete. Multivariable‐adjusted Cox regression analyses with a fixed follow‐up time were based on 2368 men and 2657 women with complete parental survival data and relevant confounders to calculate risk ratios (RR) of reaching longevity.

Results

In age‐adjusted models, paternal and maternal age at death were significantly positively associated with reaching 90 years in both male and female offspring. In male offspring, paternal age at death (≥90 years vs <80 years) showed the strongest association with survival to 90 years (RR 1.42, 95% CI 1.07–1.89), after confounder correction. In female offspring, maternal age at death (≥90 years vs <80 years) showed the strongest association with survival to 90 years (RR 1.20, 95% CI 1.04–1.40).

Discussion

After confounder adjustment, stronger and significant associations were observed between paternal lifespan and male offspring longevity, and maternal lifespan and female offspring longevity. Future research should investigate through which pathways a longer lifespan of parents is transmitted to their offspring. Geriatr Gerontol Int 2021; 21: 215–221.

Multiple-Tissue Integrative Transcriptome-Wide Association Studies Discovered New Genes Associated With Amyotrophic Lateral Sclerosis

Genome-wide association studies (GWAS) have identified multiple causal genes associated with amyotrophic lateral sclerosis (ALS); however, the genetic architecture of ALS remains completely unknown and a large number of causal genes have yet been discovered. To full such gap in part, we implemented an integrative analysis of transcriptome-wide association study (TWAS) for ALS to prioritize causal genes with summary statistics from 80,610 European individuals and employed 13 GTEx brain tissues as reference transcriptome panels. The summary-level TWAS analysis with single brain tissue was first undertaken and then a flexible p-value combination strategy, called summary data-based Cauchy Aggregation TWAS (SCAT), was proposed to pool association signals from single-tissue TWAS analysis while protecting against highly positive correlation among tests. Extensive simulations demonstrated SCAT can produce well-calibrated p-value for the control of type I error and was often much more powerful to identify association signals across various scenarios compared with single-tissue TWAS analysis. Using SCAT, we replicated three ALS-associated genes (i.e., ATXN3, SCFD1, and C9orf72) identified in previous GWASs and discovered additional five genes (i.e., SLC9A8, FAM66D, TRIP11, JUP, and RP11-529H20.6) which were not reported before. Furthermore, we discovered the five associations were largely driven by genes themselves and thus might be new genes which were likely related to the risk of ALS. However, further investigations are warranted to verify these results and untangle the pathophysiological function of the genes in developing ALS.

Stress-sensing in the human greying hair follicle: Ataxia Telangiectasia Mutated (ATM) depletion in hair bulb melanocytes in canities-prone scalp

Canities (or hair greying) is an age-linked loss of the natural pigment called melanin from hair. While the specific cause(s) underlying the loss of melanogenically-active melanocytes from the anagen hair bulbs of affected human scalp remains unclear, oxidative stress sensing appears to be a key factor involved. In this study, we examined the follicular melanin unit in variably pigmented follicles from the aging human scalp of healthy individuals (22-70 years). Over 20 markers were selected within the following categories: melanocyte-specific, apoptosis, cell cycle, DNA repair/damage, senescence and oxidative stress. As expected, a reduction in melanocyte-specific markers in proportion to the extent of canities was observed. A major finding of our study was the intense and highly specific nuclear expression of Ataxia Telangiectasia Mutated (ATM) protein within melanocytes in anagen hair follicle bulbs. ATM is a serine/threonine protein kinase that is recruited and activated by DNA double-strand breaks and functions as an important sensor of reactive oxygen species (ROS) in human cells. The incidence and expression level of ATM correlated with pigmentary status in canities-affected hair follicles. Moreover, increased staining of the redox-associated markers 8-OHdG, GADD45 and GP-1 were also detected within isolated bulbar melanocytes, although this change was not clearly associated with donor age or canities extent. Surprisingly, we were unable to detect any specific change in the expression of other markers of oxidative stress, senescence or DNA damage/repair in the canities-affected melanocytes compared to surrounding bulbar keratinocytes. By contrast, several markers showed distinct expression of markers for oxidative stress and apoptosis/differentiation in the inner root sheath (IRS) as well as other parts of the hair follicle. Using our in vitro model of primary human scalp hair follicle melanocytes, we showed that ATM expression increased after incubation with the pro-oxidant hydrogen peroxide (H₂O₂). In addition, this ATM increase was prevented by pre-incubation of cells with antioxidants. The relationship between ATM and redox stress sensing was further evidenced as we observed that the inhibition of ATM expression by chemical inhibition promoted the loss of melanocyte viability induced by oxidative stress. Taken together these new findings illustrate the key role of ATM in the protection of human hair follicle melanocytes from oxidative stress/damage within the human scalp hair bulb. In conclusion, these results highlight the remarkable complexity and role of redox sensing in the status of human hair follicle growth, differentiation and pigmentation.

Genome-Wide Gene-by-Smoking Interaction Study of Chronic Obstructive Pulmonary Disease

Risk of chronic obstructive pulmonary disease (COPD) is determined by both cigarette smoking and genetic susceptibility, but little is known about gene-by-smoking interactions. We performed a genome-wide association analysis of 179,689 controls and 21,077 COPD cases from UK Biobank subjects of European ancestry recruited from 2006 to 2010, considering genetic main effects and gene-by-smoking interaction effects simultaneously (2-degrees-of-freedom (df) test) as well as interaction effects alone (1-df interaction test). We sought to replicate significant results in COPDGene (United States, 2008-2010) and SpiroMeta Consortium (multiple countries, 1947-2015) data. We considered 2 smoking variables: 1) ever/never and 2) current/noncurrent. In the 1-df test, we identified 1 genome-wide significant locus on 15q25.1 (cholinergic receptor nicotinic β4 subunit, or CHRNB4) for ever- and current smoking and identified PI*Z allele (rs28929474) of serpin family A member 1 (SERPINA1) for ever-smoking and 3q26.2 (MDS1 and EVI1 complex locus, or MECOM) for current smoking in an analysis of previously reported COPD loci. In the 2-df test, most of the significant signals were also significant for genetic marginal effects, aside from 16q22.1 (sphingomyelin phosphodiesterase 3, or SMPD3) and 19q13.2 (Egl-9 family hypoxia inducible factor 2, or EGLN2). The significant effects at 15q25.1 and 19q13.2 loci, both previously described in prior genome-wide association studies of COPD or smoking, were replicated in COPDGene and SpiroMeta. We identified interaction effects at previously reported COPD loci; however, we failed to identify novel susceptibility loci.

Smoking, obesity, and their co-occurrence in the U.S. military veterans: results from the national health and resilience in veterans study

BACKGROUND

Smoking and obesity are major public health concerns, though little is known about the mental and physical health burden of co-occurring obesity and smoking.

METHODS

Using a nationally representative sample of U.S. military veterans, we examined the prevalence of mental and physical co-morbidities, physical and mental functioning, and quality of life between obese only; smoking only; and obese smokers.

RESULTS

Among current smokers, 31.7% were obese; among obese veterans, 16.4% were current smokers; and in the total sample, 5.4% were obese and current smokers. Relative to the obese-only group, obese smokers were more likely to be younger, male, non-white, non-married, unemployed and VA-served, and have lower household incomes. These also reported higher levels of perceived stress and trauma and were more likely to endorsed current suicidal ideation and lifetime suicide attempts (odds ratio [OR]=2.0), medical (2.3<=OR<=3.9) and psychiatric (1.5<=OR<=2.9) comorbidities, and lower overall health status and quality of life. Compared to the smoking-only group, obese smokers were more likely to endorse current suicidal ideation (OR=2.0) and nicotine dependence (OR=1.5), and reported poorer physical health and overall quality of life. Analyses were adjusted for sociodemographic and military characteristics.

LIMITATIONS

The cross-sectional study design precludes causal inference.

CONCLUSIONS

These findings suggest that co-occurring obesity and smoking is associated with substantial mental and physical health burden in U.S. veterans. Collectively, they underscore the importance of multicomponent interventions targeting, obesity, smoking, and co-occurring issues, such as trauma and internalizing disorders, in this population.

Conditional and unconditional genome-wide association study reveal complicate genetic architecture of human body weight and impacts of smoking

To reveal the impacts of smoking on genetic architecture of human body weight, we conducted a genome-wide association study on 5,336 subjects in four ethnic populations from MESA (The Multi-Ethnic Study of Atherosclerosis) data. A full genetic model was applied to association mapping for analyzing genetic effects of additive, dominance, epistasis, and their ethnicity-specific effects. Both the unconditional model (base) and conditional model including smoking as a cofactor were investigated. There were 10 SNPs involved in 96 significant genetic effects detected by the base model, which accounted for a high heritability (61.78%). Gene ontology analysis revealed that a number of genetic factors are related to the metabolic pathway of benzopyrene, a main compound in cigarettes. Smoking may play important roles in genetic effects of dominance, dominance-related epistasis, and gene-ethnicity interactions on human body weight. Gene effect prediction shows that the genetic effects of smoking cessation on body weight vary from different populations.

Translating GWAS-identified loci for cardiac rhythm and rate using an in vivo image- and CRISPR/Cas9-based approach

A meta-analysis of genome-wide association studies (GWAS) identified eight loci that are associated with heart rate variability (HRV), but candidate genes in these loci remain uncharacterized. We developed an image- and CRISPR/Cas9-based pipeline to systematically characterize candidate genes for HRV in live zebrafish embryos. Nine zebrafish orthologues of six human candidate genes were targeted simultaneously in eggs from fish that transgenically express GFP on smooth muscle cells (Tg[acta2:GFP]), to visualize the beating heart. An automated analysis of repeated 30 s recordings of beating atria in 381 live, intact zebrafish embryos at 2 and 5 days post-fertilization highlighted genes that influence HRV (hcn4 and si:dkey-65j6.2 [KIAA1755]); heart rate (rgs6 and hcn4); and the risk of sinoatrial pauses and arrests (hcn4). Exposure to 10 or 25 µM ivabradine—an open channel blocker of HCNs—for 24 h resulted in a dose-dependent higher HRV and lower heart rate at 5 days post-fertilization. Hence, our screen confirmed the role of established genes for heart rate and rhythm (RGS6 and HCN4); showed that ivabradine reduces heart rate and increases HRV in zebrafish embryos, as it does in humans; and highlighted a novel gene that plays a role in HRV (KIAA1755).

Prevalence and correlates of overweight and abdominal adiposity amongst adults residing in Madeira Autonomous Region: a cross-sectional, population-based study

Background:

Data on nutritional status and its risk factors amongst the adult population of the Madeira Autonomous Region (RAM) is scarce. This study aims to investigate the prevalence of, and risk factors associated with overweight and abdominal adiposity, assessed through measuring body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) indexes.

Methods:

Cross-sectional study using a representative sample of 911 subjects (18–64 years) from the RAM Dietary Habits of Adult Population Study. Logistic regression models were conducted to investigate the association between body mass index, WC, and WHtR indexes, with sociodemographic and lifestyle characteristics.

Results:

The prevalence of overweight amongst adults was 60.0% [95% confidence interval (CI): 56.8–63.2]. The prevalence of abdominal adiposity, assessed by WC and WHtR indexes, was 62.6% (95% CI: 59.4–65.7) and 71.9% (95% CI: 69.0–74.8), respectively. In adjusted models, age and self-reported chronic diseases were associated with both overweight and abdominal adiposity. Women were less likely to be overweight [odds ratio (OR) = 0.7 (95% CI: 0.5–0.9); P = .012] but more likely to have increased WC [OR = 2.9 (95% CI: 2.1–4.0); P < .001], compared to men. Being married was positively associated to being overweight [OR = 1.5 (95% CI: 1.1–2.1); P = .013] and increased WC [OR = 1.8 (95% CI: 1.3–2.6); P < .001], but not with WHtR index. Education level was only associated with WHtR index. Inverse associations were found for each abdominal obesity indicators and smoking status.

Conclusions:

Overweight and abdominal adiposity should be considered 2 major public health problems, amongst adult population of the RAM. Older less educated adults, with smoking habits may be considered a target group for health promotion interventions.

Estimation of non-null SNP effect size distributions enables the detection of enriched genes underlying complex traits

Traditional univariate genome-wide association studies generate false positives and negatives due to difficulties distinguishing associated variants from variants with spurious nonzero effects that do not directly influence the trait. Recent efforts have been directed at identifying genes or signaling pathways enriched for mutations in quantitative traits or case-control studies, but these can be computationally costly and hampered by strict model assumptions. Here, we present gene-ε, a new approach for identifying statistical associations between sets of variants and quantitative traits. Our key insight is that enrichment studies on the gene-level are improved when we reformulate the genome-wide SNP-level null hypothesis to identify spurious small-to-intermediate SNP effects and classify them as non-causal. gene-ε efficiently identifies enriched genes under a variety of simulated genetic architectures, achieving greater than a 90% true positive rate at 1% false positive rate for polygenic traits. Lastly, we apply gene-ε to summary statistics derived from six quantitative traits using European-ancestry individuals in the UK Biobank, and identify enriched genes that are in biologically relevant pathways.

Exome Sequencing Identifies Genes and Gene Sets Contributing to Severe Childhood Obesity, Linking PHIP Variants to Repressed POMC Transcription

Obesity is genetically heterogeneous with monogenic and complex polygenic forms. Using exome and targeted sequencing in 2,737 severely obese cases and 6,704 controls, we identified three genes (PHIP, DGKI, and ZMYM4) with an excess burden of very rare predicted deleterious variants in cases. In cells, we found that nuclear PHIP (pleckstrin homology domain interacting protein) directly enhances transcription of pro-opiomelanocortin (POMC), a neuropeptide that suppresses appetite. Obesity-associated PHIP variants repressed POMC transcription. Our demonstration that PHIP is involved in human energy homeostasis through transcriptional regulation of central melanocortin signaling has potential diagnostic and therapeutic implications for patients with obesity and developmental delay. Additionally, we found an excess burden of predicted deleterious variants involving genes nearest to loci from obesity genome-wide association studies. Genes and gene sets influencing obesity with variable penetrance provide compelling evidence for a continuum of causality in the genetic architecture of obesity, and explain some of its missing heritability.

Early pregnancy dyslipidemia is associated with placental DNA methylation at loci relevant for cardiometabolic diseases

Aim: To identify placental DNA methylation changes that are associated with early pregnancy maternal dyslipidemia. Materials & methods: We analyzed placental genome-wide DNA methylation (n = 262). Genes annotating differentially methylated CpGs were evaluated for gene expression in placenta (n = 64). Results: We found 11 novel significant differentially methylated CpGs associated with high total cholesterol, low-density lipoprotein cholesterol and triglycerides, and low high-density lipoprotein cholesterol. High triglycerides were associated with decreased methylation of cg02785814 (ALX4) and decreased expression of ALX4 in placenta. Genes annotating the differentially methylated CpGs play key roles in lipid metabolism and were enriched in dyslipidemia pathways. Functional annotation found cis-methylation quantitative trait loci for genetic loci in ALX4 and EXT2. Conclusion: Our findings lend novel insights into potential placental epigenetic mechanisms linked with maternal dyslipidemia. Trial Registration: ClinicalTrials.gov, NCT00912132.

The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019

The GWAS Catalog delivers a high-quality curated collection of all published genome-wide association studies enabling investigations to identify causal variants, understand disease mechanisms, and establish targets for novel therapies. The scope of the Catalog has also expanded to targeted and exome arrays with 1000 new associations added for these technologies. As of September 2018, the Catalog contains 5687 GWAS comprising 71673 variant-trait associations from 3567 publications. New content includes 284 full P-value summary statistics datasets for genome-wide and new targeted array studies, representing 6 × 10⁹ individual variant-trait statistics. In the last 12 months, the Catalog's user interface was accessed by ∼90000 unique users who viewed >1 million pages. We have improved data access with the release of a new RESTful API to support high-throughput programmatic access, an improved web interface and a new summary statistics database. Summary statistics provision is supported by a new format proposed as a community standard for summary statistics data representation. This format was derived from our experience in standardizing heterogeneous submissions, mapping formats and in harmonizing content. Availability: https://www.ebi.ac.uk/gwas/.

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.

Genome-wide association identifies seven loci for pelvic organ prolapse in Iceland and the UK Biobank

Pelvic organ prolapse (POP) is a downward descent of one or more of the pelvic organs, resulting in a protrusion of the vaginal wall and/or uterus. We performed a genome-wide association study of POP using data from Iceland and the UK Biobank, a total of 15,010 cases with hospital-based diagnosis code and 340,734 female controls, and found eight sequence variants at seven loci associating with POP (P < 5 × 10-8); seven common (minor allele frequency >5%) and one with minor allele frequency of 4.87%. Some of the variants associating with POP also associated with traits of similar pathophysiology. Of these, rs3820282, which may alter the estrogen-based regulation of WNT4, also associates with leiomyoma of uterus, gestational duration and endometriosis. Rs3791675 at EFEMP1, a gene involved in connective tissue homeostasis, also associates with hernias and carpal tunnel syndrome. Our results highlight the role of connective tissue metabolism and estrogen exposure in the etiology of POP.

A unified method for rare variant analysis of gene-environment interactions

Advanced technology in whole-genome sequencing has offered the opportunity to comprehensively investigate the genetic contribution, particularly rare variants, to complex traits. Several region-based tests have been developed to jointly model the marginal effect of rare variants, but methods to detect gene-environment (GE) interactions are underdeveloped. Identifying the modification effects of environmental factors on genetic risk poses a considerable challenge. To tackle this challenge, we develop a method to detect GE interactions for rare variants using generalized linear mixed effect model. The proposed method can accommodate either binary or continuous traits in related or unrelated samples. Under this model, genetic main effects, GE interactions, and sample relatedness are modeled as random effects. We adopt a kernel-based method to leverage the joint information across rare variants and implement variance component score tests to reduce the computational burden. Our simulation studies of continuous and binary traits show that the proposed method maintains correct type I error rates and appropriate power under various scenarios, such as genotype main effects and GE interaction effects in opposite directions and varying the proportion of causal variants in the model. We apply our method in the Framingham Heart Study to test GE interaction of smoking on body mass index or overweight status and replicate the Cholinergic Receptor Nicotinic Beta 4 gene association reported in previous large consortium meta-analysis of single nucleotide polymorphism-smoking interaction. Our proposed set-based GE test is computationally efficient and is applicable to both binary and continuous phenotypes, while appropriately accounting for familial or cryptic relatedness.

Insights into the aetiology of snoring from observational and genetic investigations in the UK Biobank

Although snoring is common in the general population, its aetiology has been largely understudied. Here we report a genetic study on snoring (n ~ 408,000; snorers ~ 152,000) using data from the UK Biobank. We identify 42 genome-wide significant loci, with an SNP-based heritability estimate of ~10% on the liability scale. Genetic correlations with body mass index, alcohol intake, smoking, schizophrenia, anorexia nervosa and neuroticism are observed. Gene-based associations identify 173 genes, including DLEU7, MSRB3 and POC5, highlighting genes expressed in the brain, cerebellum, lungs, blood and oesophagus. We use polygenic scores (PGS) to predict recent snoring and probable obstructive sleep apnoea (OSA) in an independent Australian sample (n ~ 8000). Mendelian randomization analyses suggest a potential causal relationship between high BMI and snoring. Altogether, our results uncover insights into the aetiology of snoring as a complex sleep-related trait and its role in health and disease beyond it being a cardinal symptom of OSA.

Snoring is common in the population and tends to be more prevalent in older and/or male individuals. Here, the authors perform GWAS for habitual snoring, identify 41 genomic loci and explore potential causal relationships with anthropometric and cardiometabolic disease traits.

Novel and Known Gene-Smoking Interactions With cIMT Identified as Potential Drivers for Atherosclerosis Risk in West-African Populations of the AWI-Gen Study

Introduction

Atherosclerosis is a key contributor to the burden of cardiovascular diseases (CVDs) and many epidemiological studies have reported on the effect of smoking on carotid intima-media thickness (cIMT) and its subsequent effect on CVD risk. Gene-environment interaction studies have contributed towards understanding some of the missing heritability of genome-wide association studies. Gene-smoking interactions on cIMT have been studied in non-African populations (European, Latino-American, and African American) but no comparable African research has been reported. Our aim was to investigate smoking-SNP interactions on cIMT in two West African populations by genome-wide analysis.

Materials and methods

Only male participants from Burkina Faso (Nanoro = 993) and Ghana (Navrongo = 783) were included, as smoking was extremely rare among women. Phenotype and genotype data underwent stringent QC and genotype imputation was performed using the Sanger African Imputation Panel. Smoking prevalence among men was 13.3% in Nanoro and 42.5% in Navrongo. We analyzed gene-smoking interactions with PLINK after adjusting for covariates: age and 6 PCs (Model 1); age, BMI, blood pressure, fasting glucose, cholesterol levels, MVPA, and 6 PCs (Model 2). All analyses were performed at site level and for the combined data set.

Results

In Nanoro, we identified new gene-smoking interaction variants for cIMT within the previously described RCBTB1 region (rs112017404, rs144170770, and rs4941649) (Model 1: p = 1.35E-07; Model 2: p = 3.08E-08). In the combined sample, two novel intergenic interacting variants were identified, rs1192824 in the regulatory region of TBC1D8 (p = 5.90E-09) and rs77461169 (p = 4.48E-06) located in an upstream region of open chromatin. In silico functional analysis suggests the involvement of genes implicated in biological processes related to cell or biological adhesion and regulatory processes in gene-smoking interactions with cIMT (as evidenced by chromatin interactions and eQTLs).

Discussion

This is the first gene-smoking interaction study for cIMT, as a risk factor for atherosclerosis, in sub-Saharan African populations. In addition to replicating previously known signals for RCBTB1, we identified two novel genomic regions (TBC1D8, near BCHE) involved in this gene-environment interaction.

A Comprehensive Genome-Wide and Phenome-Wide Examination of BMI and Obesity in a Northern Nevadan Cohort

The aggregation of Electronic Health Records (EHR) and personalized genetics leads to powerful discoveries relevant to population health. Here we perform genome-wide association studies (GWAS) and accompanying phenome-wide association studies (PheWAS) to validate phenotype-genotype associations of BMI, and to a greater extent, severe Class 2 obesity, using comprehensive diagnostic and clinical data from the EHR database of our cohort. Three GWASs of 500,000 variants on the Illumina platform of 6,645 Healthy Nevada participants identified several published and novel variants that affect BMI and obesity. Each GWAS was followed with two independent PheWASs to examine associations between extensive phenotypes (incidence of diagnoses, condition, or disease), significant SNPs, BMI, and incidence of extreme obesity. The first GWAS examines associations with BMI in a cohort with no type 2 diabetics, focusing exclusively on BMI. The second GWAS examines associations with BMI in a cohort that includes type 2 diabetics. In the second GWAS, type 2 diabetes is a comorbidity, and thus becomes a covariate in the statistical model. The intersection of significant variants of these two studies is surprising. The third GWAS is a case vs. control study, with cases defined as extremely obese (Class 2 or 3 obesity), and controls defined as participants with BMI between 18.5 and 25. This last GWAS identifies strong associations with extreme obesity, including established variants in the FTO and NEGR1 genes, as well as loci not yet linked to obesity. The PheWASs validate published associations between BMI and extreme obesity and incidence of specific diagnoses and conditions, yet also highlight novel links. This study emphasizes the importance of our extensive longitudinal EHR database to validate known associations and identify putative novel links with BMI and obesity.

Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals.

RESULTS

Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Identification of a 1p21 independent functional variant for abdominal obesity

OBJECTIVES

Aiming to uncover the genetic basis of abdominal obesity, we performed a genome-wide association study (GWAS) meta-analysis of trunk fat mass adjusted by trunk lean mass (TFMadj) and followed by a series of functional investigations.

SUBJECTS

A total of 11,569 subjects from six samples were included into the GWAS meta-analysis.

METHODS

Meta-analysis was performed by a weighted fixed-effects model. In silico replication analysis was performed in the UK-Biobank (UKB) sample (N = 331,093) and in the GIANT study (N up to 110,204). Cis-expression QTL (cis-eQTL) analysis, dual-luciferase reporter assay and electrophoresis mobility shift assay (EMSA) were conducted to examine the functional relevance of the identified SNPs. At last, differential gene expression analysis (DGEA) was performed.

RESULTS

We identified an independent SNP rs12409479 at 1p21 (MAF = 0.07, p = 7.26 × 10-10), whose association was replicated by the analysis of TFM in the UKB sample (one-sided p = 3.39 × 10-3), and was cross-validated by the analyses of BMI (one-sided p = 0.03) and WHRadj (one-sided p = 0.04) in the GIANT study. Cis-eQTL analysis demonstrated that allele A at rs12409479 was positively associated with PTBP2 expression level in subcutaneous adipose tissue (N = 385, p = 4.15 × 10-3). Dual-luciferase reporter assay showed that the region repressed PTBP2 gene expression by downregulating PTBP2 promoter activity (p < 0.001), and allele A at rs12409479 induced higher luciferase activity than allele G did (p = 4.15 × 10-3). EMSA experiment implied that allele A was more capable of binding to unknown transcription factors than allele G. Lastly, DGEA showed that the level of PTBP2 expression was higher in individuals with obesity than in individuals without obesity (N = 20 and 11, p = 0.04 and 9.22 × 10-3), suggesting a regulatory role in obesity development.

CONCLUSIONS

Taken together, we hypothesize a regulating path from rs12409479 to trunk fat mass development through its allelic specific regulation of PTBP2 gene expression, thus providing some novel insight into the genetic basis of abdominal obesity.

Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.

Sleep duration is associated with an adverse lipid profile. Here, the authors perform genome-wide gene-by-sleep interaction analysis and find 49 previously unreported lipid loci when considering short or long total sleep time.

Detailed Functional Characterization of a Waist-Hip Ratio Locus in 7p15.2 Defines an Enhancer Controlling Adipocyte Differentiation

We combined CAGE sequencing in human adipocytes during differentiation with data from genome-wide association studies to identify an enhancer in the SNX10 locus on chromosome 7, presumably involved in body fat distribution. Using reporter assays and CRISPR-Cas9 gene editing in human cell lines, we characterized the role of the enhancer in adipogenesis. The enhancer was active during adipogenesis and responded strongly to insulin and isoprenaline. The allele associated with increased waist-hip ratio in human genetic studies was associated with higher enhancer activity. Mutations of the enhancer resulted in less adipocyte differentiation. RNA sequencing of cells with disrupted enhancer showed reduced expression of established adipocyte markers, such as ADIPOQ and LPL, and identified CHI3L1 on chromosome 1 as a potential gene involved in adipocyte differentiation. In conclusion, we identified and characterized an enhancer in the SNX10 locus and outlined its plausible mechanisms of action and downstream targets.

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An enhancer active during adipogenesis is located in an obesity GWAS locus

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The enhancer responded strongly to insulin and isoprenaline

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Mutation of the enhancer by CRISPR-Cas9 decreased adipocyte differentiation

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Knockout of CHI3L1 decreased adipocyte differentiation