A Large-Scale Genome-Wide Study of Gene-Sleep Duration Interactions for Blood Pressure in 811,405 Individuals from Diverse Populations

Although both short and long sleep duration are associated with elevated hypertension risk, our understanding of their interplay with biological pathways governing blood pressure remains limited. To address this, we carried out genome-wide cross-population gene-by-short-sleep and long-sleep duration interaction analyses for three blood pressure traits (systolic, diastolic, and pulse pressure) in 811,405 individuals from diverse population groups. We discover 22 novel gene-sleep duration interaction loci for blood pressure, mapped to genes involved in neurological, thyroidal, bone metabolism, and hematopoietic pathways. Non-overlap between short sleep (12) and long sleep (10) interactions underscores the plausibility of distinct influences of both sleep duration extremes in cardiovascular health. With several of our loci reflecting specificity towards population background or sex, our discovery sheds light on the importance of embracing granularity when addressing heterogeneity entangled in gene-environment interactions, and in therapeutic design approaches for blood pressure management.

Mendelian randomization with incomplete measurements on the exposure in the Hispanic Community Health Study/Study of Latinos

Mendelian randomization has been widely used to assess the causal effect of a heritable exposure variable on an outcome of interest, using genetic variants as instrumental variables. In practice, data on the exposure variable can be incomplete due to high cost of measurement and technical limits of detection. In this paper, we propose a valid and efficient method to handle both unmeasured and undetectable values of the exposure variable in one-sample Mendelian randomization analysis with individual-level data. We estimate the causal effect of the exposure variable on the outcome using maximum likelihood estimation and develop an expectation maximization algorithm for the computation of the estimator. Simulation studies show that the proposed method performs well in making inference on the causal effect. We apply our method to the Hispanic Community Health Study/Study of Latinos, a community-based prospective cohort study, and estimate the causal effect of several metabolites on phenotypes of interest.

Dietary and supplemental intake of vitamins C and E is associated with altered DNA methylation in an epigenome-wide association study meta-analysis

BACKGROUND

Dietary intake of antioxidants such as vitamins C and E protect against oxidative stress, and may also be associated with altered DNA methylation patterns.

METHODS

We meta-analysed epigenome-wide association study (EWAS) results from 11,866 participants across eight population-based cohorts to evaluate the association between self-reported dietary and supplemental intake of vitamins C and E with DNA methylation. EWAS were adjusted for age, sex, BMI, caloric intake, blood cell type proportion, smoking status, alcohol consumption, and technical covariates. Significant results of the meta-analysis were subsequently evaluated in gene set enrichment analysis (GSEA) and expression quantitative trait methylation (eQTM) analysis.

RESULTS

In meta-analysis, methylation at 4,656 CpG sites was significantly associated with vitamin C intake at FDR ≤ 0.05. The most significant CpG sites associated with vitamin C (at FDR ≤ 0.01) were enriched for pathways associated with systems development and cell signalling in GSEA, and were associated with downstream expression of genes enriched in the immune response in eQTM analysis. Furthermore, methylation at 160 CpG sites was significantly associated with vitamin E intake at FDR ≤ 0.05, but GSEA and eQTM analysis of the top most significant CpG sites associated with vitamin E did not identify significant enrichment of any biological pathways investigated.

CONCLUSIONS

We identified significant associations of many CpG sites with vitamin C and E intake, and our results suggest that vitamin C intake may be associated with systems development and the immune response.

Associations between avocado intake and measures of glucose and insulin homeostasis in Hispanic individuals with and without type 2 diabetes: Results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

BACKGROUND AND AIMS

To investigate associations between avocado intake and glycemia in adults with Hispanic/Latino ancestry.

METHODS AND RESULTS

The associations of avocado intake with measures of insulin and glucose homeostasis were evaluated in a cross-sectional analysis of up to 14,591 Hispanic/Latino adults, using measures of: average glucose levels (hemoglobin A1c; HbA1c), fasting glucose and insulin, glucose and insulin levels after an oral glucose tolerance test (OGTT), and calculated measures of insulin resistance (HOMA-IR, and HOMA-%β), and insulinogenic index. Associations were assessed using multivariable linear regression models, which controlled for sociodemographic factors and health behaviors, and which were stratified by dysglycemia status. In those with normoglycemia, avocado intake was associated with a higher insulinogenic index (β = 0.17 ± 0.07, P = 0.02). In those with T2D (treated and untreated), avocado intake was associated with lower hemoglobin A1c (HbA1c; β = -0.36 ± 0.21, P = 0.02), and lower fasting glucose (β = -0.27 ± 0.12, P = 0.02). In the those with untreated T2D, avocado intake was additionally associated with HOMA-%β (β = 0.39 ± 0.19, P = 0.04), higher insulin values 2-h after an oral glucose load (β = 0.62 ± 0.23, P = 0.01), and a higher insulinogenic index (β = 0.42 ± 0.18, P = 0.02). No associations were observed in participants with prediabetes.

CONCLUSIONS

We observed an association of avocado intake with better glucose/insulin homeostasis, especially in those with T2D.

Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts

Inadequate representation of non-European ancestry populations in genome-wide association studies (GWAS) has limited opportunities to isolate functional variants. Fine-mapping in multi-ancestry populations should improve the efficiency of prioritizing variants for functional interrogation. To evaluate this hypothesis, we leveraged ancestry architecture to perform comparative GWAS and fine-mapping of obesity-related phenotypes in European ancestry populations from the UK Biobank (UKBB) and multi-ancestry samples from the Population Architecture for Genetic Epidemiology (PAGE) consortium with comparable sample sizes. In the investigated regions with genome-wide significant associations for obesity-related traits, fine-mapping in our ancestrally diverse sample led to 95% and 99% credible sets (CS) with fewer variants than in the European ancestry sample. Lead fine-mapped variants in PAGE regions had higher average coding scores, and higher average posterior probabilities for causality compared to UKBB. Importantly, 99% CS in PAGE loci contained strong expression quantitative trait loci (eQTLs) in adipose tissues or harbored more variants in tighter linkage disequilibrium (LD) with eQTLs. Leveraging ancestrally diverse populations with heterogeneous ancestry architectures, coupled with functional annotation, increased fine-mapping efficiency and performance, and reduced the set of candidate variants for consideration for future functional studies. Significant overlap in genetic causal variants across populations suggests generalizability of genetic mechanisms underpinning obesity-related traits across populations.

Influence of alcohol consumption and alcohol metabolism variants on breast cancer risk among Black women: results from the AMBER consortium

BACKGROUND

Moderate to heavy alcohol consumption is associated with an increased risk of breast cancer. The etiologic role of genetic variation in genes involved in ethanol metabolism has not been established, with little information available among women of African ancestry.

METHODS

Our analysis from the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium included 2889 U.S. Black women who were current drinkers at the time of breast cancer diagnosis (N cases = 715) and had available genetic data for four ethanol metabolism genomic regions (ADH, ALDH, CYP2E1, and ALDH2). We used generalized estimating equations to calculate genetic effects, gene* alcohol consumption (≥ 7drinks/week vs. < 7/week) interactions, and joint main plus interaction effects of up to 23,247 variants in ethanol metabolism genomic regions on odds of breast cancer.

RESULTS

Among current drinkers, 21% of cases and 14% of controls reported consuming ≥ 7 drinks per week. We identified statistically significant genetic effects for rs79865122-C in CYP2E1 with odds of ER- breast cancer and odds of triple negative breast cancer, as well as a significant joint effect with odds of ER- breast cancer (≥ 7drinks per week OR = 3.92, < 7 drinks per week OR = 0.24, p_joint = 3.74 × 10^-6). In addition, there was a statistically significant interaction of rs3858704-A in ALDH2 with consumption of ≥ 7 drinks/week on odds of triple negative breast cancer (≥ 7drinks per week OR = 4.41, < 7 drinks per week OR = 0.57, p_int = 8.97 × 10^-5).

CONCLUSIONS

There is a paucity of information on the impact of genetic variation in alcohol metabolism genes on odds of breast cancer among Black women. Our analysis of variants in four genomic regions harboring ethanol metabolism genes in a large consortium of U.S. Black women identified significant associations between rs79865122-C in CYP2E1 and odds of ER- and triple negative breast cancer. Replication of these findings is warranted.

Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing

Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.

Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.

Genetic diversity fuels gene discovery for tobacco and alcohol use

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Rare genetic variants explain missing heritability in smoking

Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.

Erratum: Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium

[This corrects the article DOI: 10.1016/j.xhgg.2022.100099.].

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention

Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

Do adverse childhood experiences and genetic obesity risk interact in relation to body mass index in young adulthood? Findings from the National Longitudinal Study of Adolescent to Adult Health

BACKGROUND

Few studies have focused on the role of adverse childhood experiences (ACEs) in relation to genetic susceptibility to obesity.

OBJECTIVE

We aimed to examine the interaction between the presence of ACEs (i.e., physical, psychological and sexual abuse) before the age of 18 and BMI polygenic score.

METHODS

Data came from the National Longitudinal Study of Adolescent to Adult Health (Add Health) Wave IV (2007/2008) where saliva samples were collected for DNA genotyping and information on BMI and ACEs were obtained from 5854 European American (EA), 2073 African American (AA) and 1448 Hispanic American (HA) participants aged 24 to 32 years old. Polygenic scores were calculated as the sum of the number of risk alleles of BMI-related SNPs which were weighted by effect size. A race/ethnicity-stratified mixed-effects linear regression model was used to test for differential association between BMI polygenic score and BMI by the presence of ACEs.

RESULTS

We did not find any evidence of significant interaction between ACEs and polygenic score in relation to BMI among EA (p = 0.289), AA (p = 0.618) or HA (p = 0.870). In main effects models, polygenic score was positively associated with BMI in all race/ethnic groups, yet the presence of ACEs was associated with increased BMI only among EA.

CONCLUSION

We did not find any evidence that ACEs exacerbate genetic predisposition to increased BMI in early adulthood.

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.

Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits

One mechanism by which genetic factors influence complex traits and diseases is altering gene expression. Direct measurement of gene expression in relevant tissues is rarely tenable; however, genetically regulated gene expression (GReX) can be estimated using prediction models derived from large multi-omic datasets. These approaches have led to the discovery of many gene-trait associations, but whether models derived from predominantly European ancestry (EA) reference panels can map novel associations in ancestrally diverse populations remains unclear. We applied PrediXcan to impute GReX in 51,520 ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) participants (35% African American, 45% Hispanic/Latino, 10% Asian, and 7% Hawaiian) across 25 key cardiometabolic traits and relevant tissues to identify 102 novel associations. We then compared associations in PAGE to those in a random subset of 50,000 White British participants from UK Biobank (UKBB50k) for height and body mass index (BMI). We identified 517 associations across 47 tissues in PAGE but not UKBB50k, demonstrating the importance of diverse samples in identifying trait-associated GReX. We observed that variants used in PrediXcan models were either more or less differentiated across continental-level populations than matched-control variants depending on the specific population reflecting sampling bias. Additionally, variants from identified genes specific to either PAGE or UKBB50k analyses were more ancestrally differentiated than those in genes detected in both analyses, underlining the value of population-specific discoveries. This suggests that while EA-derived transcriptome imputation models can identify new associations in non-EA populations, models derived from closely matched reference panels may yield further insights. Our findings call for more diversity in reference datasets of tissue-specific gene expression.

Deterring illegal smartphone use while driving: Are perceptions of risk information associated with the impact of informal sanctions?

Advertising campaigns have used threat appeals to increase the perceptions of risk associated with dangerous driving behaviours. Building on recent research that suggests increasing the pertinence of informal sanctions (sense of guilt, fear of peer disapproval, or fear of hurting oneself and others) decreases the likelihood of illegal smartphone engagement while driving, this study aimed to determine if perceptions of risk information, that is, how effective drivers believe the information is in deterring their illegal use, is associated with perceptions of informal sanctions. An online survey of 1027 Victorians who self-reported illegal smartphone use while driving asked participants to rate the personal deterrent effectiveness of five types of risks associated with illegal smartphone use while driving. A hierarchical linear regression model explored the associations between the most effective risks and each informal sanction. Female drivers were more likely than male drivers to experience guilt, fear of social loss and fear of physical loss when using their smartphones illegally. More frequent illegal smartphone engagement while driving was associated with decreased impact of informal sanctions. Female drivers were more likely than male drivers to perceive each risk as effective. The most effective piece of information was, "Contributes to 16% of Victorian road deaths and serious injuries annually"; it was also the least known (32.7% males, 26.7% females). This message, alongside, "Increases risk of a crash comparable to those associated with driving under the influence of alcohol or cannabis" and, "A 2 s glance at your phone while driving at 50 km/h effectively means driving blind for 27 m", were associated with stronger perceptions of guilt, fear of peer disapproval, or fear of hurting oneself and others when thinking about using a smartphone illegally while driving. These results suggest tailoring and targeting these specific risk information may be effective in deterring illegal smartphone use while driving.

The power of genetic diversity in genome-wide association studies of lipids

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

"Does that mean I can't use my phone to pay when I'm in the Maccas drive thru?": Younger drivers' uncertainty and attitude toward smartphone law and punishment

This study employed a mixed methods approach (a survey [n = 2,774] and focus groups [n = 16]) to understand the perceptions of younger drivers (18-25) on current smartphone laws in the Australian state of Victoria. First, by analysing quantitative data gathered from an online survey regarding smartphone laws, perceptions of punishment when breaking the law, and attitudes to both the law and fines, this study found younger drivers were less likely to understand the law around phone use while driving, even after direct or indirect experience with police. Additionally, the severity and impact of fines were perceived as more impactful and severe among younger drivers, women, and those on lower incomes, and the most common types of illegal use younger drivers engaged with were navigation, music applications, and hands-free calling, mostly facilitated through Bluetooth with their device placed out of sight. Consequently, focus groups were conducted with a subset of these younger drivers to explore these findings in more depth. It was revealed that smartphone laws were perceived to be ambiguous, at times unreasonable, and difficult to access conclusive information regarding the law or receive information throughout the Graduated Licencing Program. Additionally, of full licenced drivers breaking smartphone laws (n = 807), 61.7 percent never used a cradle. Among probationary drivers breaking the law (n = 209), 76.1 percent never used a cradle. This suggests rampant surreptitious illegal use. As such, younger drivers learning to drive are also learning methods to avoid punishment while breaking smartphone laws. This included not using a cradle and opting instead for Bluetooth connectivity or engaging in hand-held use, a choice that continued into Full Licensed driving. The severity of punishment was not common knowledge and was perceived to be incommensurate to the risks associated with certain types of use. In their opinion all of these factors reduced the legitimacy of the law. Addressing these factors with evidence-based countermeasures may increase compliance and road safety.

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.

Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations

BACKGROUND

Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed.

METHODS

To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants.

RESULTS

Our results revealed 24 suggestive signals (p < 1 × 10-4) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN.

CONCLUSIONS

These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.

Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10^-16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.

Self-reported mindfulness, cyclist anger and aggression

Anger is a common behaviour exhibited by road users when one's goals are perceived to have been blocked by another. Recent research has demonstrated that, generally, cyclists tend to deal with anger in constructive ways. However, when anger does manifest, it can result in behaviours that increase their crash risk. Amongst motor vehicle drivers, mindfulness levels have been associated with less anger and appear to mediate anger and associated aggression. The current study sought to understand whether mindfulness has similar associations with anger and aggression in a sample of cyclists. A total of 583 cyclists (males = 68 %) completed an online questionnaire that sought information on their levels of mindfulness, current mindfulness practices and tendencies for anger and aggression while cycling. The relationships between these were then examined using structural equation modelling. The results showed that cyclists with higher mindfulness levels tended to report less anger across a range of situations (e.g., interactions with pedestrians, cyclists, motor vehicle drivers and police). Both direct and indirect (through anger) relationships were found between mindfulness and aggression, again showing that more mindful cyclists tended to engage in less frequent aggression. These findings align with recent research investigating this relationship amongst motor vehicle drivers and suggest that mindfulness may be a promising strategy to reduce or avoid anger and aggression in cyclists.

Understanding the deterrent impact formal and informal sanctions have on illegal smartphone use while driving

The illegal use of a smartphone while driving increases the risk of crashes. As such, road authorities rely on countermeasures to reduce illegal smartphone use. Deterrence-based methods dominate road safety, however, perceptions and impact of formal (legal) and informal (non-legal) methods to deter illegal smartphone use in Australia have not yet been explored. The current study reports on a survey of 2774 drivers (47.0 % males) that own and regularly use a smartphone. The survey analysed the self-reported frequency of illegal smartphone use while driving, perceptions of formal and informal deterrence mechanisms, differences between perceived and informed deterrence, and deterrent predictors of illegal use. The findings revealed that illegal smartphone use is increasing in Victoria, Australia. Drivers that break the law perceive deterrent mechanisms significantly different from drivers that abide by the law, however, both groups view the prospect of hurting oneself as most impactful. Additionally, drivers tend to underestimate the consequences of illegal use, yet overestimate the certainty of apprehension. A binary logistic regression analysis revealed that only age, gender and informal sanctions such as social loss (stigma/peer disapproval), internal loss (shame/guilt/embarrassment), and physical loss (injury/property damage) were significant predictors of illegal use. None of the formal mechanisms were significant. Based on these findings, road safety interventions and future research should consider exploring the psychological characteristics of young people's perceptions of informal sanctions such as social loss (shame/embarrassment) and internal loss (guilt).

Importance of Genetic Studies of Cardiometabolic Disease in Diverse Populations

Genome-wide association studies have revolutionized our understanding of the genetic underpinnings of cardiometabolic disease. Yet, the inadequate representation of individuals of diverse ancestral backgrounds in these studies may undercut their ultimate potential for both public health and precision medicine. The goal of this review is to describe the imperativeness of studying the populations who are most affected by cardiometabolic disease, to the aim of better understanding the genetic underpinnings of the disease. We support this premise by describing the current variation in the global burden of cardiometabolic disease and emphasize the importance of building a globally and ancestrally representative genetics evidence base for the identification of population-specific variants, fine-mapping, and polygenic risk score estimation. We discuss the important ethical, legal, and social implications of increasing ancestral diversity in genetic studies of cardiometabolic disease and the challenges that arise from the (1) lack of diversity in current reference populations and available analytic samples and the (2) unequal generation of health-associated genomic data and their prediction accuracies. Despite these challenges, we conclude that additional, unprecedented opportunities lie ahead for public health genomics and the realization of precision medicine, provided that the gap in diversity can be systematically addressed. Achieving this goal will require concerted efforts by social, academic, professional and regulatory stakeholders and communities, and these efforts must be based on principles of equity and social justice.

Quality of dietary fat and genetic risk of type 2 diabetes: individual participant data meta-analysis

OBJECTIVE

To investigate whether the genetic burden of type 2 diabetes modifies the association between the quality of dietary fat and the incidence of type 2 diabetes.

DESIGN

Individual participant data meta-analysis.

DATA SOURCES

Eligible prospective cohort studies were systematically sourced from studies published between January 1970 and February 2017 through electronic searches in major medical databases (Medline, Embase, and Scopus) and discussion with investigators.

REVIEW METHODS

Data from cohort studies or multicohort consortia with available genome-wide genetic data and information about the quality of dietary fat and the incidence of type 2 diabetes in participants of European descent was sought. Prospective cohorts that had accrued five or more years of follow-up were included. The type 2 diabetes genetic risk profile was characterized by a 68-variant polygenic risk score weighted by published effect sizes. Diet was recorded by using validated cohort-specific dietary assessment tools. Outcome measures were summary adjusted hazard ratios of incident type 2 diabetes for polygenic risk score, isocaloric replacement of carbohydrate (refined starch and sugars) with types of fat, and the interaction of types of fat with polygenic risk score.

RESULTS

Of 102 305 participants from 15 prospective cohort studies, 20 015 type 2 diabetes cases were documented after a median follow-up of 12 years (interquartile range 9.4-14.2). The hazard ratio of type 2 diabetes per increment of 10 risk alleles in the polygenic risk score was 1.64 (95% confidence interval 1.54 to 1.75, I²=7.1%, τ²=0.003). The increase of polyunsaturated fat and total omega 6 polyunsaturated fat intake in place of carbohydrate was associated with a lower risk of type 2 diabetes, with hazard ratios of 0.90 (0.82 to 0.98, I²=18.0%, τ²=0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I²=58.8%, τ²=0.001; per increment of 1 g/d), respectively. Increasing monounsaturated fat in place of carbohydrate was associated with a higher risk of type 2 diabetes (hazard ratio 1.10, 95% confidence interval 1.01 to 1.19, I²=25.9%, τ²=0.006; per 5% of energy). Evidence of small study effects was detected for the overall association of polyunsaturated fat with the risk of type 2 diabetes, but not for the omega 6 polyunsaturated fat and monounsaturated fat associations. Significant interactions between dietary fat and polygenic risk score on the risk of type 2 diabetes (P>0.05 for interaction) were not observed.

CONCLUSIONS

These data indicate that genetic burden and the quality of dietary fat are each associated with the incidence of type 2 diabetes. The findings do not support tailoring recommendations on the quality of dietary fat to individual type 2 diabetes genetic risk profiles for the primary prevention of type 2 diabetes, and suggest that dietary fat is associated with the risk of type 2 diabetes across the spectrum of type 2 diabetes genetic risk.

Exome-Derived Adiponectin-Associated Variants Implicate Obesity and Lipid Biology

Circulating levels of adiponectin, an adipocyte-secreted protein associated with cardiovascular and metabolic risk, are highly heritable. To gain insights into the biology that regulates adiponectin levels, we performed an exome array meta-analysis of 265,780 genetic variants in 67,739 individuals of European, Hispanic, African American, and East Asian ancestry. We identified 20 loci associated with adiponectin, including 11 that had been reported previously (p < 2 × 10^-7). Comparison of exome array variants to regional linkage disequilibrium (LD) patterns and prior genome-wide association study (GWAS) results detected candidate variants (r² > .60) spanning as much as 900 kb. To identify potential genes and mechanisms through which the previously unreported association signals act to affect adiponectin levels, we assessed cross-trait associations, expression quantitative trait loci in subcutaneous adipose, and biological pathways of nearby genes. Eight of the nine loci were also associated (p < 1 × 10^-4) with at least one obesity or lipid trait. Candidate genes include PRKAR2A, PTH1R, and HDAC9, which have been suggested to play roles in adipocyte differentiation or bone marrow adipose tissue. Taken together, these findings provide further insights into the processes that influence circulating adiponectin levels.

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genetic analyses of diverse populations improves discovery for complex traits

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry^1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific^4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations^11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions¹³-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.

Genetics of Obesity in Diverse Populations

PURPOSE OF REVIEW

The prevalence of obesity continues to rise, fueling a global public health crisis characterized by dramatic increases in type 2 diabetes, cardiovascular disease, and many cancers. In the USA, several minority populations, who bear much of the obesity burden (47% in African Americans and Hispanic/Latinos, compared to 38% in European descent groups), are particularly at risk of downstream chronic disease. Compounding these disparities, most genome-wide association studies (GWAS)-including those of obesity-have largely been conducted in populations of European or East Asian ancestry. In fact, analysis of the GWAS Catalog found that while the proportion of participants of non-European or non-Asian descent had risen from 4% in 2009 to 19% in 2016, African-ancestry participants are still just 3% of GWAS, Hispanic/Latinos are < 0.5%, and other ancestries are < 0.3% or not represented at all. This review summarizes recent developments in obesity genomics in US minority populations, with the goal of reducing obesity health disparities and improving public health programs and access to precision medicine.

RECENT FINDINGS

GWAS of populations with the highest burden of obesity are essential to narrow candidate variants for functional follow-up, to identify additional ancestry-specific variants that contribute to individual genetic susceptibility, and to advance both public health and precision medicine approaches to obesity. Given the global public health burden posed by obesity and downstream chronic conditions which disproportionately affect non-European populations, GWAS of obesity-related traits in diverse populations is essential to (1) locate causal variants in GWAS-identified regions through fine mapping, (2) identify variants which influence obesity across ancestries through generalization, and (3) discover novel ancestry-specific variants which may be low frequency in European populations but common in other groups. Recent efforts to expand obesity genomic studies to understudied and underserved populations, including AAAGC, PAGE, and HISLA, are working to reduce obesity health disparities, improve public health, and bring the promise of precision medicine to all.

Complex patterns of direct and indirect association between the transcription Factor-7 like 2 gene, body mass index and type 2 diabetes diagnosis in adulthood in the Hispanic Community Health Study/Study of Latinos

Background

Genome-wide association studies have implicated the transcription factor 7-like 2 (TCF7L2) gene in type 2 diabetes risk, and more recently, in decreased body mass index. Given the contrary direction of genetic effects on these two traits, it has been suggested that the observed association with body mass index may reflect either selection bias or a complex underlying biology at TCF7L2.

Methods

Using 9031 Hispanic/Latino adults (21–76 years) with complete weight history and genetic data from the community-based Hispanic Community Health Study/Study of Latinos (HCHS/SOL, Baseline 2008–2011), we estimated the multivariable association between the additive number of type 2 diabetes increasing-alleles at TCF7L2 (rs7903146-T) and body mass index. We then used structural equation models to simultaneously model the genetic association on changes in body mass index across the life course and estimate the odds of type 2 diabetes per TCF7L2 risk allele.

Results

We observed both significant increases in type 2 diabetes prevalence at examination (independent of body mass index) and decreases in mean body mass index and waist circumference across genotypes at rs7903146. We observed a significant multivariable association between the additive number of type 2 diabetes-risk alleles and lower body mass index at examination. In our structured modeling, we observed non-significant inverse direct associations between rs7903146-T and body mass index at ages 21 and 45 years, and a significant positive association between rs7903146-T and type 2 diabetes onset in both middle and late adulthood.

Conclusions

Herein, we replicated the protective effect of rs7930146-T on body mass index at multiple time points in the life course, and observed that these effects were not explained by past type 2 diabetes status in our structured modeling. The robust replication of the negative effects of TCF7L2 on body mass index in multiple samples, including in our diverse Hispanic/Latino community-based sample, supports a growing body of literature on the complex biologic mechanism underlying the functional consequences of TCF7L2 on obesity and type 2 diabetes across the life course.

Electronic supplementary material

The online version of this article (10.1186/s40608-018-0200-x) contains supplementary material, which is available to authorized users.

Characterization of the contribution of shared environmental and genetic factors to metabolic syndrome methylation heritability and familial correlations

Background

Transgenerational epigenetic inheritance has been posited as a possible contributor to the observed heritability of metabolic syndrome (MetS). Yet the extent to which estimates of epigenetic inheritance for DNA methylation sites are inflated by environmental and genetic covariance within families is still unclear. We applied current methods to quantify the environmental and genetic contributors to the observed heritability and familial correlations of four previously associated MetS methylation sites at three genes (CPT1A, SOCS3 and ABCG1) using real data made available through the GAW20.

Results

Our findings support the role of both shared environment and genetic variation in explaining the heritability of MetS and the four MetS cytosine-phosphate-guanine (CpG) sites, although the resulting heritability estimates were indistinguishable from one another. Familial correlations by type of relative pair generally followed our expectation based on relatedness, but in the case of sister and parent pairs we observed nonsignificant trends toward greater correlation than expected, as would be consistent with the role of shared environmental factors in the inflation of our estimated correlations.

Conclusions

Our work provides an interesting and flexible statistical framework for testing models of epigenetic inheritance in the context of human family studies. Future work should endeavor to replicate our findings and advance these methods to more robustly describe epigenetic inheritance patterns in human populations.

A survey of microRNA single nucleotide polymorphisms identifies novel breast cancer susceptibility loci in a case-control, population-based study of African-American women

BACKGROUND

MicroRNAs (miRNAs) regulate gene expression and influence cancer. Primary transcripts of miRNAs (pri-miRNAs) are poorly annotated and little is known about the role of germline variation in miRNA genes and breast cancer (BC). We sought to identify germline miRNA variants associated with BC risk and tumor subtype among African-American (AA) women.

METHODS

Under the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium, genotyping and imputed data from four studies on BC in AA women were combined into a final dataset containing 224,188 miRNA gene single nucleotide polymorphisms (SNPs) for 8350 women: 3663 cases and 4687 controls. The primary miRNA sequence was identified for 566 miRNA genes expressed in Encyclopedia of DNA Elements (ENCODE) Tier 1 cell types and human pancreatic islets. Association analysis was conducted using logistic regression for BC status overall and by tumor subtype.

RESULTS

A novel BC signal was localized to an 8.6-kb region of 17q25.3 by four SNPs (rs9913477, rs1428882938, rs28585511, and rs7502931) and remained statistically significant after multiple test correction (odds ratio (OR) = 1.44, 95% confidence interval (CI) = 1.26-1.65; p = 3.15 × 10-7; false discovery rate (FDR) = 0.03). These SNPs reside in a genomic location that includes both the predicted primary transcript of the noncoding miRNA gene MIR3065 and the first intron of the gene for brain-specific angiogenesis inhibitor 1-associated protein 2 (BAIAP2). Furthermore, miRNA-associated SNPs on chromosomes 1p32.3, 5q32, and 3p25.1 were the strongest signals for hormone receptor, luminal versus basal-like, and HER2 enrichment status, respectively. A second phase of genotyping (1397 BC cases, 2418 controls) that included two SNPs in the 8.6-kb region was used for validation and meta-analysis. While neither rs4969239 nor rs9913477 was validated, when meta-analyzed with the original dataset their association with BC remained directionally consistent (OR = 1.29, 95% CI = 1.16-1.44 (p = 4.18 × 10-6) and OR = 1.33, 95% CI = 1.17-1.51 (p = 1.6 × 10-5), respectively).

CONCLUSION

Germline genetic variation indicates that MIR3065 may play an important role in BC development and heterogeneity among AA women. Further investigation to determine the potential functional effects of these SNPs is warranted. This study contributes to our understanding of BC risk in AA women and highlights the complexity in evaluating variation in gene-dense regions of the human genome.

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article.

Human factors enablers and barriers for successful airway management - an in-depth interview study

Human factors are the individual, team, environmental and organisational aspects of the anaesthetic environment that affect performance and decision-making of anaesthesia teams. This study aimed to identify which human factors were enablers and/or barriers to anaesthesia teams during airway management challenges. Sixteen interviews were conducted with experienced anaesthetists and anaesthetic nurses using an in-depth interview technique (the Critical Decision Method) to identify human factors enablers and/or barriers during successful management of a significant airway challenge. Thematic analysis identified three overarching enablers: equipment location and storage; experience and learning; teamwork and communication. Five overarching barriers were also identified: time and resource limitations; teamwork and communication; equipment location and storage; experience and learning; insufficient back-up planning; and equipment preparation. This study showed that a variety of human factors issues affect the handling of airway challenges, ranging from individual and team to organisational and environmental aspects. Recommendations for the design of airway management decision support tools that relate to equipment standardisation, decision support complexity, inclusive mutual learning and teamwork are discussed.

Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway: a meta-analysis

AIMS/HYPOTHESIS

Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits.

METHODS

Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway.

RESULTS

In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β ± SE 0.014 ± 0.004 [mmol/l], p = 1.5 × 10^-3) and higher fasting insulin (0.030 ± 0.005 [log _e pmol/l], p = 2.0 × 10^-10). No significant interactions on glycaemic traits were observed between SSB intake and selected SNPs. While a suggestive interaction was observed in the discovery cohorts with a SNP (rs1542423) in the β-Klotho (KLB) locus on fasting insulin (0.030 ± 0.011 log _e pmol/l, uncorrected p = 0.006), results in the replication cohorts and combined meta-analyses were non-significant.

CONCLUSIONS/INTERPRETATION

In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis.

TRIAL REGISTRATION

Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses' Health Study).

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent

SCOPE

Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption.

METHODS AND RESULTS

A genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction <10^-7) , and six independent variants (LINC01512-rs7751666, PALM2/AKAP2-rs914359, ACTA2-rs1388, PPP1R12A-rs7961195, LINC00333-rs9635058, AC098847.1-rs1791355) were evaluated meta-analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3' of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 × 10^-8) such that each serving of low-fat dairy was associated with 0.225 kg m^-2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2-rs1388) approached interaction replication significance for low-fat dairy exposure.

CONCLUSION

Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight.

Genetic identification of a common collagen disease in puerto ricans via identity-by-descent mapping in a health system

Achieving confidence in the causality of a disease locus is a complex task that often requires supporting data from both statistical genetics and clinical genomics. Here we describe a combined approach to identify and characterize a genetic disorder that leverages distantly related patients in a health system and population-scale mapping. We utilize genomic data to uncover components of distant pedigrees, in the absence of recorded pedigree information, in the multi-ethnic BioMe biobank in New York City. By linking to medical records, we discover a locus associated with both elevated genetic relatedness and extreme short stature. We link the gene, COL27A1, with a little-known genetic disease, previously thought to be rare and recessive. We demonstrate that disease manifests in both heterozygotes and homozygotes, indicating a common collagen disorder impacting up to 2% of individuals of Puerto Rican ancestry, leading to a better understanding of the continuum of complex and Mendelian disease.

Diseases often run in families. These disease are frequently linked to changes in DNA that are passed down through generations. Close family members may share these disease-causing mutations; so may distant relatives who inherited the same mutation from a common ancestor long ago. Geneticists use a method called linkage mapping to trace a disease found in multiple members of a family over generations to genetic changes in a shared ancestor. This allows scientists to pinpoint the exact place in the genome the disease-causing mutation occurred. Using computer algorithms, scientists can apply the same technique to identify mutations that distant relatives inherited from a common ancestor.

Belbin et al. used this computational technique to identify a mutation that may cause unusually short stature or bone and joint problems in up to 2% of people of Puerto Rican descent. In the experiments, the genomes of about 32,000 New Yorkers who have volunteered to participate in the BioMe Biobank and their health records were used to search for genetic changes linked to extremely short stature. The search revealed that people who inherited two copies of this mutation from their parents were likely to be extremely short or to have bone and joint problems. People who inherited one copy had an increased likelihood of joint or bone problems.

This mutation affects a gene responsible for making a form of protein called collagen that is important for bone growth. The analysis suggests the mutation first arose in a Native American ancestor living in Puerto Rico around the time that European colonization began. The mutation had previously been linked to a disorder called Steel syndrome that was thought to be rare. Belbin et al. showed this condition is actually fairly common in people whose ancestors recently came from Puerto Rico, but may often go undiagnosed by their physicians. The experiments emphasize the importance of including diverse populations in genetic studies, as studies of people of predominantly European descent would likely have missed the link between this disease and mutation.

Toward best practice in Human Machine Interface design for older drivers: A review of current design guidelines

Older adults are the fastest growing segment of the driving population. While there is a strong emphasis for older people to maintain their mobility, the safety of older drivers is a serious community concern. Frailty and declines in a range of age-related sensory, cognitive, and physical impairments can place older drivers at an increased risk of crash-related injuries and death. A number of studies have indicated that in-vehicle technologies such as Advanced Driver Assistance Systems (ADAS) and In-Vehicle Information Systems (IVIS) may provide assistance to older drivers. However, these technologies will only benefit older drivers if their design is congruent with the complex needs and diverse abilities of this driving cohort. The design of ADAS and IVIS is largely informed by automotive Human Machine Interface (HMI) guidelines. However, it is unclear to what extent the declining sensory, cognitive and physical capabilities of older drivers are addressed in the current guidelines. This paper provides a review of key current design guidelines for IVIS and ADAS with respect to the extent they address age-related changes in functional capacities. The review revealed that most of the HMI guidelines do not address design issues related to older driver impairments. In fact, in many guidelines driver age and sensory cognitive and physical impairments are not mentioned at all and where reference is made, it is typically very broad. Prescriptive advice on how to actually design a system so that it addresses the needs and limitations of older drivers is not provided. In order for older drivers to reap the full benefits that in-vehicle technology can afford, it is critical that further work establish how older driver limitations and capabilities can be supported by the system design process, including their inclusion into HMI design guidelines.

Evidence for Association between SH2B1 Gene Variants and Glycated Hemoglobin in Nondiabetic European American Young Adults: The Add Health Study

Glycated hemoglobin (HbA1c) is used to classify glycaemia and type 2 diabetes (T2D). Body mass index (BMI) is a predictor of HbA1c levels and T2D. We tested 43 established BMI and obesity loci for association with HbA1c in a nationally representative multiethnic sample of young adults from the National Longitudinal Study of Adolescent to Adult Health [Add Health: age 24-34 years; n = 5641 European Americans (EA); 1740 African Americans (AA); 1444 Hispanic Americans (HA)] without T2D, using two levels of covariate adjustment (Model 1: age, sex, smoking, and geographic region; Model 2: Model 1 covariates plus BMI). Bonferroni adjustment was made for 43 SNPs and we considered P < 0.0011 statistically significant. Means (SD) for HbA1c were 5.4% (0.3) in EA, 5.7% (0.4) in AA, and 5.5% (0.3) in HA. We observed significant evidence for association with HbA1c for two variants near SH2B1 in EA (rs4788102, P = 2.2 × 10(-4) ; rs7359397, P = 9.8 × 10(-4) ) for Model 1. Both results were attenuated after adjustment for BMI (rs4788102, P = 1.7 × 10(-3) ; rs7359397, P = 4.6 × 10(-3) ). No variant reached Bonferroni-corrected significance in AA or HA. These results suggest that SH2B1 polymorphisms are associated with HbA1c, largely independent of BMI, in EA young adults.

No relevant impact of ambient temperature on disability measurements in a large cohort of patients with multiple sclerosis

BACKGROUND AND PURPOSE

Many patients with multiple sclerosis (MS) report a worsening of symptoms due to high ambient temperatures, but objective data about this association are rare and contradictory. The aim of this study was to investigate the influence of ambient temperature on standard clinical tests.

METHODS

We extracted the Symbol Digit Modality Test, Nine Hole Peg Test, Timed 25 Foot Walk (T25FW), Timed Tandem Walk, Expanded Disability Status Scale (EDSS) and quality-of-life items on cognition, fatigue and depression from our clinical database and matched them to historical temperatures. We used linear mixed-effect models to investigate the association between temperature and outcomes.

RESULTS

A total of 1254 patients with MS (mean age, 42.7 years; 69.9% females; 52.1% relapsing-remitting MS, mean EDSS, 3.8) had 5751 assessments between 1996 and 2012. We observed a worsening in the T25FW with higher ambient temperatures in moderately disabled patients (EDSS ≥ 4) but not in less disabled patients. However, an increase of 10°C prolonged the T25FW by just 0.4 s. Other outcomes were not associated with ambient temperatures.

CONCLUSIONS

Higher ambient temperature might compromise walking capabilities in patients with MS with a manifest walking impairment. However, effects are small and not detectable in mildly disabled patients. Hand function, cognition, mood and fatigue do not appear to be correlated with ambient temperature.

Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Rare and low-frequency coding variants alter human adult height

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.

BMI loci and longitudinal BMI from adolescence to young adulthood in an ethnically diverse cohort

Objective

The association of obesity susceptibility variants with change in body mass index (BMI) across the life course is not well understood.

Subjects

In ancestry stratified models of 5,962 European American (EA), 2,080 African American (AA), and 1,582 Hispanic American (HA) individuals from the National Longitudinal Study of Adolescent to Adult Health (Add Health), we examined associations between 34 obesity SNPs with per year change in BMI, measured by the slope from a growth-curve analysis of two or more BMI measurements between adolescence and young adulthood. For SNPs nominally associated with BMI change (p<0.05), we interrogated age differences within data collection Wave and time differences between age categories that overlapped between Waves.

Results

We found SNPs in/near FTO, MC4R, MTCH2, TFAP2B, SEC16B, and TMEM18 were significantly associated (p<0.0015 ≈ 0.05/34) with BMI change in EA and the ancestry-combined meta-analysis. Rs9939609 in FTO met genome-wide significance at p<5e-08 in the EA and ancestry combined analysis, respectively [Beta(se)=0.025(0.004);Beta(se)=0.021(0.003)]. No SNPs were significant after Bonferroni correction in AA or HA, although 5 SNPs in AA and 4 SNPs in HA were nominally significant (p<0.05). In EA and the ancestry-combined meta-analysis, rs3817334 near MTCH2 showed larger effects in younger respondents, while rs987237 near TFAP2B, showed larger effects in older respondents across all Waves. Differences in effect estimates across time for MTCH2 and TFAP2B are suggestive of either era or cohort effects.

Conclusion

The observed association between variants in/near FTO, MC4R, MTCH2, TFAP2B, SEC16B, and TMEM18 with change in BMI from adolescence to young adulthood suggest that the genetic effect of BMI loci varies over time in a complex manner, highlighting the importance of investigating loci influencing obesity risk across the life course.

The interaction between physical activity and obesity gene variants in association with BMI: Does the obesogenic environment matter?

Little is known about how obesity susceptibility single nucleotide polymorphisms (SNPs) interact with moderate to vigorous physical activity (MVPA) in relation to BMI during adolescence, once obesogenic neighborhood factors are accounted for. In race stratified models, including European (EA; N=4977), African (AA; N=1726), and Hispanic Americans (HA; N=1270) from the National Longitudinal Study of Adolescent to Adult Health (1996; ages 12-21), we assessed the evidence for a SNPxMVPA interaction with BMI-for-age Z score, once accounting for obesogenic neighborhood factors including physical activity amenities, transportation and recreation infrastructure, poverty and crime. Eight SNPxMVPA interactions with suggestive significance (p<0.10; three in each EA, and AA, two in HA) were observed showing attenuation on BMI-for-age Z score in adolescents with ≥5 versus <5 bouts/week MVPA, except for rs10146997 (near NRXN3). Findings were robust to the inclusion of neighborhood-level variables as covariates. These findings suggest that any attenuation from MVPA on a genetic susceptibility to obesity during adolescence is likely not operating through obesogenic neighborhood factors.