Type 2 Diabetes Modifies the Association of CAD Genomic Risk Variants With Subclinical Atherosclerosis.

BACKGROUND: Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D. METHODS: We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test. RESULTS: Using a Bonferroni-corrected significance threshold of P<1.6×10-4, we identified 3 genes (ATP1B1, ARVCF, and LIPG) associated with CAC and 2 genes (ABCG8 and EIF2B2) associated with carotid intima-media thickness and carotid plaque, respectively, through gene-based rare variant set analysis. Both ATP1B1 and ARVCF also had significantly different associations for CAC in T2D cases versus controls. No significant interaction tests were identified through the candidate single-variant analysis. CONCLUSIONS: These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC.

Clonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk.

OBJECTIVE: Clonal hematopoiesis of indeterminate potential (CHIP) is an aging-related accumulation of somatic mutations in hematopoietic stem cells, leading to clonal expansion. CHIP presence has been implicated in atherosclerotic coronary heart disease (CHD) and all-cause mortality, but its association with incident type 2 diabetes (T2D) is unknown. We hypothesized that CHIP is associated with elevated risk of T2D. RESEARCH DESIGN AND METHODS: CHIP was derived from whole-genome sequencing of blood DNA in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) prospective cohorts. We performed analysis for 17,637 participants from six cohorts, without prior T2D, cardiovascular disease, or cancer. We evaluated baseline CHIP versus no CHIP prevalence with incident T2D, including associations with DNMT3A, TET2, ASXL1, JAK2, and TP53 variants. We estimated multivariable-adjusted hazard ratios (HRs) and 95% CIs with adjustment for age, sex, BMI, smoking, alcohol, education, self-reported race/ethnicity, and combined cohorts' estimates via fixed-effects meta-analysis. RESULTS: Mean (SD) age was 63.4 (11.5) years, 76% were female, and CHIP prevalence was 6.0% (n = 1,055) at baseline. T2D was diagnosed in n = 2,467 over mean follow-up of 9.8 years. Participants with CHIP had 23% (CI 1.04, 1.45) higher risk of T2D than those with no CHIP. Specifically, higher risk was for TET2 (HR 1.48; CI 1.05, 2.08) and ASXL1 (HR 1.76; CI 1.03, 2.99) mutations; DNMT3A was nonsignificant (HR 1.15; CI 0.93, 1.43). Statistical power was limited for JAK2 and TP53 analyses. CONCLUSIONS: CHIP was associated with higher incidence of T2D. CHIP mutations located on genes implicated in CHD and mortality were also related to T2D, suggesting shared aging-related pathology.

Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits.

Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry. ARTICLE HIGHLIGHTS: We aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

Alternatives to in vitro fertilization.

There have been concerns on the potential overuse of in vitro fertilization (IVF) in view of the lack of evidence on effectiveness in certain populations, potential short and long-term safety risks, and economic considerations. On the other hand, the use of alternatives to IVF seems to be underappreciated in clinical practice as well as research. In this review, we summarized the up-to-date evidence on the effectiveness, safety as well as cost-effectiveness of different alternatives to IVF, including expectant management, intrauterine insemination, tubal flushing, in vitro maturation as well as intravaginal culture. We also discussed the trend of IVF use over the last decade and the available tiers of service because of intravaginal culture, and revisited the roles of different alternatives to IVF in modern reproductive medicine from both clinical and research perspectives.

Managing One's Age in Age-Dissimilar Mentoring Relationships.

The aging of the workforce creates opportunities for experienced employees to share expertise with newer employees, via mentoring relationships. Age-dissimilar interactions, however, like those between mentor and protégé, can engender challenging interpersonal dynamics such as concern about how others view and respond to them. The current study examines the unique challenges and opportunities of age-dissimilar mentoring relationships, using a sample of doctor and lawyer protégés. Findings suggest that age dissimilarity does not play as large of a role in mentoring relationship outcomes as age-related behaviors. How one manages their age seems to be more important, such that managing one's age in a positive way by redefining age-related stereotypes rather than switching attention away from stereotypes is better for mentoring relationship outcomes no matter the age difference between mentor and protégé. Implications, inferences, and limitations are discussed.

Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification.

Coronary artery calcification (CAC) is a measure of atherosclerosis and a well-established predictor of coronary artery disease (CAD) events. Here we describe a genome-wide association study (GWAS) of CAC in 22,400 participants from multiple ancestral groups. We confirmed associations with four known loci and identified two additional loci associated with CAC (ARSE and MMP16), with evidence of significant associations in replication analyses for both novel loci. Functional assays of ARSE and MMP16 in human vascular smooth muscle cells (VSMCs) demonstrate that ARSE is a promoter of VSMC calcification and VSMC phenotype switching from a contractile to a calcifying or osteogenic phenotype. Furthermore, we show that the association of variants near ARSE with reduced CAC is likely explained by reduced ARSE expression with the G allele of enhancer variant rs5982944. Our study highlights ARSE as an important contributor to atherosclerotic vascular calcification, and a potential drug target for vascular calcific disease.

Barriers to Weight Management Among Overweight and Obese Firefighters.

OBJECTIVE: To examine barriers to weight management among firefighters. METHODS: Health risk data collected on 2373 overweight firefighters were used for this cross-sectional study. Barriers to weight management were the dependent variables and demographic characteristics, readiness for change, and health risk factors were the correlates in the multivariate-adjusted logistic models. RESULTS: Overweight firefighters who were ready to begin a weight management program were more likely to identify "lack of knowledge about weight management," "lack of access to exercise opportunities," and "eating helps me cope with stress" and report a greater number of barriers toward weight management. Older firefighters were less likely to identify or report one or more barriers to weight management. CONCLUSION: Understanding barriers, readiness for change, and age may be useful in planning interventions to help firefighters better manage their weight.

Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program.

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.

Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls.

Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10-3) and candidate genes from knockout mice (P = 5.2 × 10-3). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.

The Continuing Evolution of Precision Health in Type 2 Diabetes: Achievements and Challenges.

PURPOSE OF REVIEW: The purpose of this review was to summarize recent advances in the genomics of type 2 diabetes (T2D) and to highlight current initiatives to advance precision health. RECENT FINDINGS: Generation of multi-omic data to measure each of the "biologic layers," developments in describing genomic function and annotation in T2D relevant tissue, along with the increasing recognition that T2D is a heterogeneous disease, and large-scale collaborations have all contributed to advancing our understanding of the molecular basis of T2D. Substantial advances have been made in understanding the molecular basis of T2D pathogenesis, such that precision health diabetes is increasingly becoming a reality. For precision diabetes to become a routine in clinical and public health, additional large-scale multi-omic initiatives are needed along with better assessment of our environment to delineate an individual's diabetes subtype for improved detection and management.

Maternal lipid profile differs by gestational diabetes physiologic subtype.

AIM: To characterize lipid profiles in women with different gestational diabetes mellitus (GDM) physiologic subtypes. METHODS: We measured seven lipid markers (total cholesterol, LDL, HDL, triglycerides, non-esterified fatty acids (NEFA), ApoA, ApoB) in fasting plasma collected in a prospective cohort of 805 pregnant women during second trimester. We estimated insulin sensitivity and secretion using oral glucose tolerance test-based validated indices. We categorized GDM physiologic subtypes by insulin sensitivity and secretion defects defined as values below the 25th percentile among women with normal glucose tolerance (NGT), as previously established. We compared lipid markers across NGT and GDM subtypes. We explored associations between lipid markers and newborn anthropometry in the overall group and stratified by glucose tolerance status. RESULTS: Among 805 women, 67 (8.3%) developed GDM. Women with GDM had higher body mass index (BMI; 29.3 vs. 26.6 kg/m2), while ethnicity (97.3% vs. 97.0% European ancestry) and age (28 vs. 29 years) were similar. In comparison to women with NGT, women with GDM characterized by a predominant insulin sensitivity defect had significantly higher triglycerides (2.20 vs. 1.82, P = 0.002), lower HDL (1.64 vs. 1.90, P = 0.01) and higher NEFA (0.34 vs. 0.24, P < 0.0001). GDM women with a predominant insulin secretion defect differed from women with NGT with respect to NEFA (0.32 vs. 0.24, P = 0.003) while other lipid markers were similar. These associations remained significant after adjusting for maternal age and BMI. Greater maternal levels of NEFA were associated with higher birth weight z-scores in women with an insulin secretion defect (BMI-adjusted r = 0.58, P = 0.01). We did not find significant associations between other lipid markers and newborn anthropometry in other groups. CONCLUSION: Women with GDM have distinct lipid profiles based on their GDM physiologic subtype which may not be apparent when investigating GDM as a single group.

Excess mortality among Indiana firefighters, 1985-2013.

BACKGROUND: Firefighters are exposed to toxic agents increasing their risk for cancer and cardiovascular disease. We examined the odds of cancer and cardiovascular mortality of firefighters relative to a matched group of non-firefighters from the general population. METHODS: Firefighter death records were matched to four non-firefighter death records on age at time of death, sex, race, ethnicity, and year of death. Exact odds ratios, 95% confidence intervals, and P-values were calculated using conditional logistic regression to compare groups. RESULTS: The odds of death due to malignant cancers was significantly higher for firefighters than non-firefighters (OR: 1.19; 95%CI 1.08, 1.30). There was no difference in the odds of death for cardiovascular diseases, including ischemic heart disease, between the two groups. CONCLUSIONS: The study suggests the importance of early and effective cancer prevention strategies among firefighters including worksite health promotion programs and incumbent physical activity evaluation.

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.

Type 2 Diabetes Genetic Risk Scores Are Associated With Increased Type 2 Diabetes Risk Among African Americans by Cardiometabolic Status.

The relationship between genetic risk variants associated with glucose homeostasis and type 2 diabetes risk has yet to be fully explored in African American populations. We pooled data from 4 prospective studies including 4622 African Americans to assess whether ß-cell dysfunction (BCD) and/or insulin resistance (IR) genetic variants were associated with increased type 2 diabetes risk. The BCD genetic risk score (GRS) and combined BCD/IR GRS were significantly associated with increased type 2 diabetes risk. In cardiometabolic-stratified models, the BCD and IR GRS were associated with increased type 2 diabetes risk among 5 cardiometabolic strata: 3 clinically healthy strata and 2 clinically unhealthy strata. Genetic risk scores related to BCD and IR were associated with increased risk of type 2 diabetes in African Americans. Notably, the GRSs were significant predictors of type 2 diabetes among individuals in clinically normal ranges of cardiometabolic traits.

Clinical characteristics and 12-month outcomes of patients with valvular and non-valvular atrial fibrillation in Kenya.

BACKGROUND: Atrial fibrillation (AF) is a major contributor to the global cardiovascular disease burden. The clinical profile and outcomes of AF patients with valvular heart diseases in sub-Saharan Africa (SSA) have not been adequately described. We assessed clinical features and 12-month outcomes of patients with valvular AF (vAF) in comparison to AF patients without valvular heart disease (nvAF) in western Kenya. METHODS: We performed a cohort study with retrospective data gathering to characterize risk factors and prospective data collection to characterize their hospitalization, stroke and mortality rates. RESULTS: The AF patients included 77 with vAF and 69 with nvAF. The mean (SD) age of vAF and nvAF patients were 37.9(14.5) and 69.4(12.3) years, respectively. There were significant differences (p<0.001) between vAF and nvAF patients with respect to female sex (78% vs. 55%), rates of hypertension (29% vs. 73%) and heart failure (10% vs. 49%). vAF patients were more likely to be taking anticoagulation therapy compared to those with nvAF (97% vs. 76%; p<0.01). After 12-months of follow-up, the overall mortality, hospitalization and stroke rates for vAF patients were high, at 10%, 34% and 5% respectively, and were similar to the rates in the nvAF patients (15%, 36%, and 5%, respectively). CONCLUSION: Despite younger age and few comorbid conditions, patients with vAF in this developing country setting are at high risk for nonfatal and fatal outcomes, and are in need of interventions to improve short and long-term outcomes.

Methodological Standards for Meta-Analyses and Qualitative Systematic Reviews of Cardiac Prevention and Treatment Studies: A Scientific Statement From the American Heart Association.

Meta-analyses are becoming increasingly popular, especially in the fields of cardiovascular disease prevention and treatment. They are often considered to be a reliable source of evidence for making healthcare decisions. Unfortunately, problems among meta-analyses such as the misapplication and misinterpretation of statistical methods and tests are long-standing and widespread. The purposes of this statement are to review key steps in the development of a meta-analysis and to provide recommendations that will be useful for carrying out meta-analyses and for readers and journal editors, who must interpret the findings and gauge methodological quality. To make the statement practical and accessible, detailed descriptions of statistical methods have been omitted. Based on a survey of cardiovascular meta-analyses, published literature on methodology, expert consultation, and consensus among the writing group, key recommendations are provided. Recommendations reinforce several current practices, including protocol registration; comprehensive search strategies; methods for data extraction and abstraction; methods for identifying, measuring, and dealing with heterogeneity; and statistical methods for pooling results. Other practices should be discontinued, including the use of levels of evidence and evidence hierarchies to gauge the value and impact of different study designs (including meta-analyses) and the use of structured tools to assess the quality of studies to be included in a meta-analysis. We also recommend choosing a pooling model for conventional meta-analyses (fixed effect or random effects) on the basis of clinical and methodological similarities among studies to be included, rather than the results of a test for statistical heterogeneity.

Disclosing a disability: Do strategy type and onset controllability make a difference?

In hiring contexts, individuals with concealable disabilities make decisions about how they should disclose their disability to overcome observers' biases. Previous research has investigated the effectiveness of binary disclosure decisions-that is, to disclose or conceal a disability-but we know little about how, why, or under what conditions different types of disclosure strategies impact observers' hiring intentions. In this article, we examine disability onset controllability (i.e., whether the applicant is seen as responsible for their disability onset) as a boundary condition for how disclosure strategy type influences the affective reactions (i.e., pity, admiration) that underlie observers' hiring intentions. Across 2 experiments, we found that when applicants are seen as responsible for their disability, strategies that de-emphasize the disability (rather than embrace it) lower observers' hiring intentions by elevating their pity reactions. Thus, the effectiveness of different types of disability disclosure strategies differs as a function of onset controllability. We discuss implications for theory and practice for individuals with disabilities and organizations. (PsycINFO Database Record

A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk.

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.

A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease.

Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to guide development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in six genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow-up in consortia. We used these data to first compare associations of variants in genes encoding drug targets with the effects of pharmacological manipulation of those targets in clinical trials. We then tested the association of those variants with disease outcomes, including coronary heart disease, to predict cardiovascular safety of these agents. A low-frequency missense variant (Ala316Thr; rs10305492) in the gene encoding glucagon-like peptide-1 receptor (GLP1R), the target of GLP1R agonists, was associated with lower fasting glucose and T2D risk, consistent with GLP1R agonist therapies. The minor allele was also associated with protection against heart disease, thus providing evidence that GLP1R agonists are not likely to be associated with an unacceptable increase in cardiovascular risk. Our results provide an encouraging signal that these agents may be associated with benefit, a question currently being addressed in randomized controlled trials. Genetic variants associated with metabolic traits and multiple disease outcomes can be used to validate therapeutic targets at an early stage in the drug development process.