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Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium. Discovery for genetic association was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, and BMI and in a model analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI (model 3). In model 3, three variants reached genome-wide significance: rs13422522 (NYAP2; P = 8.87 × 10−11), rs12454712 (BCL2; P = 2.7 × 10−8), and rs10506418 (FAM19A2; P = 1.9 × 10−8). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardiometabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci.

Background Obesity is an established risk factor for severe COVID-19 outcomes. The mechanistic underpinnings of this association are not well-understood. Objective To evaluate the mediating role of systemic inflammation in obesity-associated COVID-19 outcomes. Methods This hospital-based, observational study included 3828 SARS-CoV-2-infected patients who were hospitalized February to May 2020 at Massachusetts General Hospital (MGH) or Columbia University Irving Medical Center/New York Presbyterian Hospital (CUIMC/NYP). We use mediation analysis to evaluate whether peak inflammatory biomarkers (C-reactive protein [CRP], erythrocyte sedimentation rate [ESR], D-dimer, ferritin, white blood cell count and interleukin-6) are in the causal pathway between obesity (BMI ≥ 30) and mechanical ventilation or death within 28 days of presentation to care. Results In the MGH cohort (n = 1202), obesity was associated with greater likelihood of ventilation or death (OR = 1.73; 95% CI = [1.25, 2.41]; P = 0.001) and higher peak CRP (P Conclusion Findings support systemic inflammatory pathways in obesity-associated severe COVID-19 disease, particularly in patients

Summary Background The prevalence of overweight, obesity, and diabetes is rising rapidly in low-income and middle-income countries (LMICs), but there are scant empirical data on the association between body-mass index (BMI) and diabetes in these settings. Methods In this cross-sectional study, we pooled individual-level data from nationally representative surveys across 57 LMICs. We identified all countries in which a WHO Stepwise Approach to Surveillance (STEPS) survey had been done during a year in which the country fell into an eligible World Bank income group category. For LMICs that did not have a STEPS survey, did not have valid contact information, or declined our request for data, we did a systematic search for survey datasets. Eligible surveys were done during or after 2008; had individual-level data; were done in a low-income, lower-middle-income, or upper-middle-income country; were nationally representative; had a response rate of 50% or higher; contained a diabetes biomarker (either a blood glucose measurement or glycated haemoglobin [HbA1c]); and contained data on height and weight. Diabetes was defined biologically as a fasting plasma glucose concentration of 7·0 mmol/L (126·0 mg/dL) or higher; a random plasma glucose concentration of 11·1 mmol/L (200·0 mg/dL) or higher; or a HbA1c of 6·5% (48·0 mmol/mol) or higher, or by self-reported use of diabetes medication. We included individuals aged 25 years or older with complete data on diabetes status, BMI (defined as normal [18·5–22·9 kg/m2], upper-normal [23·0–24·9 kg/m2], overweight [25·0–29·9 kg/m2], or obese [≥30·0 kg/m2]), sex, and age. Countries were categorised into six geographical regions: Latin America and the Caribbean, Europe and central Asia, east, south, and southeast Asia, sub-Saharan Africa, Middle East and north Africa, and Oceania. We estimated the association between BMI and diabetes risk by multivariable Poisson regression and receiver operating curve analyses, stratified by sex and geographical region. Findings Our pooled dataset from 58 nationally representative surveys in 57 LMICs included 685 616 individuals. The overall prevalence of overweight was 27·2% (95% CI 26·6–27·8), of obesity was 21·0% (19·6–22·5), and of diabetes was 9·3% (8·4–10·2). In the pooled analysis, a higher risk of diabetes was observed at a BMI of 23 kg/m2 or higher, with a 43% greater risk of diabetes for men and a 41% greater risk for women compared with a BMI of 18·5–22·9 kg/m2. Diabetes risk also increased steeply in individuals aged 35–44 years and in men aged 25–34 years in sub-Saharan Africa. In the stratified analyses, there was considerable regional variability in this association. Optimal BMI thresholds for diabetes screening ranged from 23·8 kg/m2 among men in east, south, and southeast Asia to 28·3 kg/m2 among women in the Middle East and north Africa and in Latin America and the Caribbean. Interpretation The association between BMI and diabetes risk in LMICs is subject to substantial regional variability. Diabetes risk is greater at lower BMI thresholds and at younger ages than reflected in currently used BMI cutoffs for assessing diabetes risk. These findings offer an important insight to inform context-specific diabetes screening guidelines. Funding Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program.

Background We sought to develop an automatable score to predict hospitalization, critical illness, or death for patients at risk for coronavirus disease 2019 (COVID-19) presenting for urgent care. Methods We developed the COVID-19 Acuity Score (CoVA) based on a single-center study of adult outpatients seen in respiratory illness clinics or the emergency department. Data were extracted from the Partners Enterprise Data Warehouse, and split into development (n = 9381, 7 March–2 May) and prospective (n = 2205, 3–14 May) cohorts. Outcomes were hospitalization, critical illness (intensive care unit or ventilation), or death within 7 days. Calibration was assessed using the expected-to-observed event ratio (E/O). Discrimination was assessed by area under the receiver operating curve (AUC). Results In the prospective cohort, 26.1%, 6.3%, and 0.5% of patients experienced hospitalization, critical illness, or death, respectively. CoVA showed excellent performance in prospective validation for hospitalization (expected-to-observed ratio [E/O]: 1.01; AUC: 0.76), for critical illness (E/O: 1.03; AUC: 0.79), and for death (E/O: 1.63; AUC: 0.93). Among 30 predictors, the top 5 were age, diastolic blood pressure, blood oxygen saturation, COVID-19 testing status, and respiratory rate. Conclusions CoVA is a prospectively validated automatable score for the outpatient setting to predict adverse events related to COVID-19 infection., A coronavirus disease 2019 (COVID-19) outpatient screening score is developed and validated prospectively in a single-center setting. It predicts 7-day prognosis: hospitalization, intensive care/ventilation, or death, based on 30 predictors including demographics, COVID-19 status, vital signs, radiology report, and medical history.

OBJECTIVE Diabetes and obesity are highly prevalent among hospitalized patients with coronavirus disease 2019 (COVID-19), but little is known about their contributions to early COVID-19 outcomes. We tested the hypothesis that diabetes is a risk factor for poor early outcomes, after adjustment for obesity, among a cohort of patients hospitalized with COVID-19. RESEARCH DESIGN AND METHODS We used data from the Massachusetts General Hospital (MGH) COVID-19 Data Registry of patients hospitalized with COVID-19 between 11 March 2020 and 30 April 2020. Primary outcomes were admission to the intensive care unit (ICU), need for mechanical ventilation, and death within 14 days of presentation to care. Logistic regression models were adjusted for demographic characteristics, obesity, and relevant comorbidities. RESULTS Among 450 patients, 178 (39.6%) had diabetes—mostly type 2 diabetes. Among patients with diabetes versus patients without diabetes, a higher proportion was admitted to the ICU (42.1% vs. 29.8%, respectively, P = 0.007), required mechanical ventilation (37.1% vs. 23.2%, P = 0.001), and died (15.9% vs. 7.9%, P = 0.009). In multivariable logistic regression models, diabetes was associated with greater odds of ICU admission (odds ratio 1.59 [95% CI 1.01–2.52]), mechanical ventilation (1.97 [1.21–3.20]), and death (2.02 [1.01–4.03]) at 14 days. Obesity was associated with greater odds of ICU admission (2.16 [1.20–3.88]) and mechanical ventilation (2.13 [1.14–4.00]) but not with death. CONCLUSIONS Among hospitalized patients with COVID-19, diabetes was associated with poor early outcomes, after adjustment for obesity. These findings can help inform patient-centered care decision making for people with diabetes at risk for COVID-19.

Background Advancements in statistical methods and sequencing technology have led to numerous novel discoveries in human genetics in the past two decades. Among phenotypes of interest, most attention has been given to studying genetic associations with continuous or binary traits. Efficient statistical methods have been proposed and are available for both types of traits under different study designs. However, for multinomial categorical traits in related samples, there is a lack of efficient statistical methods and software. Results We propose an efficient score test to analyze a multinomial trait in family samples, in the context of genome-wide association/sequencing studies. An alternative Wald statistic is also proposed. We also extend the methodology to be applicable to ordinal traits. We performed extensive simulation studies to evaluate the type-I error of the score test, Wald test compared to the multinomial logistic regression for unrelated samples, under different allele frequency and study designs. We also evaluate the power of these methods. Results show that both the score and Wald tests have a well-controlled type-I error rate, but the multinomial logistic regression has an inflated type-I error rate when applied to family samples. We illustrated the application of the score test with an application to the Framingham Heart Study to uncover genetic variants associated with diabesity, a multi-category phenotype. Conclusion Both proposed tests have correct type-I error rate and similar power. However, because the Wald statistics rely on computer-intensive estimation, it is less efficient than the score test in terms of applications to large-scale genetic association studies. We provide computer implementation for both multinomial and ordinal traits.

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes., Sex differences in fasting glucose and insulin have been identified, but the genetic loci underlying these differences have not. Here, the authors perform a meta-analysis of genome-wide association studies to detect sex-specific and sex-dimorphic loci associated with fasting glucose and insulin.

OBJECTIVE LDL cholesterol (LDLc)-lowering drugs modestly increase body weight and type 2 diabetes risk, but the extent to which the diabetogenic effect of lowering LDLc is mediated through increased BMI is unknown. RESEARCH DESIGN AND METHODS We conducted summary-level univariable and multivariable Mendelian randomization (MR) analyses in 921,908 participants to investigate the effect of lowering LDLc on type 2 diabetes risk and the proportion of this effect mediated through BMI. We used data from 92,532 participants from 14 observational studies to replicate findings in individual-level MR analyses. RESULTS A 1-SD decrease in genetically predicted LDLc was associated with increased type 2 diabetes odds (odds ratio [OR] 1.12 [95% CI 1.01, 1.24]) and BMI (β = 0.07 SD units [95% CI 0.02, 0.12]) in univariable MR analyses. The multivariable MR analysis showed evidence of an indirect effect of lowering LDLc on type 2 diabetes through BMI (OR 1.04 [95% CI 1.01, 1.08]) with a proportion mediated of 38% of the total effect (P = 0.03). Total and indirect effect estimates were similar across a number of sensitivity analyses. Individual-level MR analyses confirmed the indirect effect of lowering LDLc on type 2 diabetes through BMI with an estimated proportion mediated of 8% (P = 0.04). CONCLUSIONS These findings suggest that the diabetogenic effect attributed to lowering LDLc is partially mediated through increased BMI. Our results could help advance understanding of adipose tissue and lipids in type 2 diabetes pathophysiology and inform strategies to reduce diabetes risk among individuals taking LDLc-lowering medications.

RationaleA commonMUC5Bgene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis, but its role in the SARS-CoV-2 infection and disease severity is unclear.ObjectivesTo assess whether rs35705950-T confers differential risk for clinical outcomes associated with COVID-19 infection among participants in the Million Veteran Program (MVP) and COVID-19 Host Genetics Initiative (HGI).MethodsMVP participants were examined for an association between the incidence or severity of COVID-19 and the presence of aMUC5Brs35705950-T allele. Comorbidities and clinical events were extracted from the electronic health records (EHR). The analysis was performed within each ancestry group in the MVP, adjusting for sex, age, age2,and first twenty principal components followed by a trans-ethnic meta-analysis. We then pursued replication and performed a meta-analysis with the trans-ethnic summary statistics from the HGI. A phenome-wide association study (PheWAS) of the rs35705950-T was conducted to explore associated pathophysiologic conditions.Measurements and Main ResultsA COVID-19 severity scale was modified from the World Health Organization criteria, and phenotypes derived from the International Classification of Disease-9/10 were extracted from EHR. Presence of rs35705950-T was associated with fewer hospitalizations (Ncases=25353, Ncontrols=631,024; OR=0.86 [0.80-0.93], p=7.4 × 10−5) in trans-ethnic meta-analysis within MVP and joint meta-analyses with the HGI (N=1641311; OR=0.89 [0.85-0.93], p =1.9 × 10−6). Moreover, individuals of European Ancestry with at least one copy of rs35705950-T had fewer post-COVID-19 pneumonia events (OR=0.85 [0.76-0.96], p =0.008). PheWAS exclusively revealed pulmonary involvement.ConclusionsTheMUC5Bvariant rs35705950-T is protective in COVID-19 infection.

Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for an equitable deployment of PRS to clinical practice that benefits global populations. Here we integrate T2D GWAS in European, African American and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and evaluate the PRS in the multi-ethnic eMERGE study, four African American cohorts, and the Taiwan Biobank. The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined, and the top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5 fold of increase in T2D risk, suggesting the potential of using the trans-ancestry PRS as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

The worldwide prevalence of type 2 diabetes (T2D) continues to increase, despite the established efficacy of T2D prevention interventions. Identifying individuals at high risk and making them the focus of preventive interventions may reduce the incidence of diabetes and global disease burden. We recently showed that T2D risk assessment in white middle-aged men and women can be improved with addition of an insulin resistance measure (assessed by HOMA of insulin resistance) to glycemia and other established risk factors (1). We have also developed an insulin resistance score (IRScore), comprising fasting insulin and C-peptide measured by mass spectrometry, to assess the probability of existing insulin resistance where insulin resistance was defined as being in the top tertile of steady-state plasma glucose level (≥198 mg/dL) (2). In the current study, we asked whether this IRScore improved T2D risk assessment beyond glycemia and established risk factors in a population of older Europeans. Older populations are of particular interest given the steady increase in the average age worldwide, especially in Europe, Japan, China, and the U.S. We conducted a case-cohort study based on the …

OBJECTIVES: Sugar-sweetened beverage (SSB) consumption is associated with a higher risk of type 2 diabetes (T2D), but the metabolic changes linking SSB consumption to T2D are not fully understood. Thus, we aimed to identify a plasma metabolomic signature of SSB consumption and evaluate its association with incident T2D. METHODS: We used liquid chromatography–mass spectrometry to measure plasma metabolites (>200) among 3,434 participants from three US cohorts: Nurses’ Health Study (NHS), NHS II, and Health Professionals Follow-up Study (HPFS). SSB consumption (servings/day; sodas, fruit punches, and other sugary drinks) was estimated from food frequency questionnaires. We used elastic net regression with 10-fold-cross-validation to identify metabolites associated with higher SSB consumption among a training set of participants (n = 2068) and replicated the association in a testing set (n = 1366). A metabolomic signature score was calculated as the weighted sum of SSB-associated metabolites. Pearson correlation (r) coefficients and 95% confidence intervals (CI) between the metabolomic signature and self-reported SSB consumption were calculated. We used multivariable Cox regression models to estimate hazard ratios (HR) and CI of the identified metabolomic signature with incident T2D among all participants. RESULTS: We identified an SSB plasma metabolomic signature of 71 metabolites, primarily lipids and amino acids. Pearson correlation (r) coefficients between self-reported SSBs and the plasma metabolomic signature were 0.18 (95% CI: 0.14, 0.22; P

Patients with type 2 diabetes (T2D) are at two-fold increased risk of cardiovascular disease (CVD), which is the leading cause of T2D morbidity and mortality. Here, we conducted a time-to-event genome-wide association study (GWAS) to identify genetic variants associated with incident CVD among patients with T2D in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. Incident CVD was defined based on a composite of myocardial infarction, stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. In each participating prospective cohort, we performed GWAS using a Cox proportional hazard survival model adjusting for age, and sex to identify genetic variants associated with incident CVD, and cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. A total of 37,327 participants were included in the analyses (26,928 European ancestry and 10,399 non-European ancestry) which comprised 6,012 primary event cases. We identified three distinct genetic loci associated with incident CVD among individuals with T2D that reached the threshold for genome-wide significance: rs231964 (intronic variant in NOX3, hazard ratio [HR] 1.4, P=8.3x10-9), rs139753656 (intronic variant in DCC, HR 2.0, P=2.4x10-8), and rs77202398 (intronic variant in TNS3, HR 1.4, P=4.4x10-8). Among 204 known coronary artery disease risk loci, 27 were associated with incident CVD with P Disclosure S. Kwak: None. P. Wu: None. J. B. Meigs: Consultant; Self; Quest Diagnostics. On behalf of the charge diabetes working group: n/a. Funding National Institutes of Health (1R01HL151855-01)

Background: We are currently facing unprecedented humanitarian crises. With diabetes at record-high levels and projected increases in humanitarian crises globally, data on the burden and management of DM in humanitarian crises is needed to stop unnecessary disability and death. Methods: We surveyed data on diabetes care provision in humanitarian medical services in 2018 across 4 humanitarian agencies (Doctors Without Borders, International Committee of the Red Cross, International Rescue Committee, United Nations High Commissioner for Refugees) with 83 randomly selected sites across 27 countries in 5 global regions. Of 83 sites, 65 (78%) reported collecting DM care data and were used for cross-sectional analysis of rates and proportions. Results: Of 65 sites, most were in the Eastern Mediterranean (n=29, 45%) and Africa (35%), with 20% elsewhere; 34% were refugee camps, 34% rural non-camp sites, 21% urban non-camp sites, 11% internally displaced persons (IDP) camps. Populations were mostly a mix of refugees, IDPs and the general population (n=46/65, 71%), with refugees only at 23% and IDPs only at 6% of sites. Of 65 sites, 58 were affected by conflict (89%), 5% epidemics, 1% natural disasters and 5% multiple crisis types. Most sites (n=49) were in protracted crises (75%), with 23% in recovery stages and 2% in acute crisis. Of 65 sites, 46 (71%) reported providing clinical DM management. However, only 66% had insulin available, 71% had capillary glucose testing, 55% urine dipstick glucose, 19% hemoglobin A1c testing, 22% home glucose monitoring, 35% community outreach, 58% patient education, 32% training of staff and 52% continuity of care systems. Conclusions: DM services were mostly provided in protracted humanitarian settings. Services were widespread but often rudimentary and delivered to the general population as well as refugees and IDPs. Improving DM care for crisis-affected populations is urgently needed. Disclosure S. Kehlenbrink: None. S. Kayden: None. K. Donelan: None. B. Porneala: None. J. B. Meigs: Consultant; Self; Quest Diagnostics. O. Mahboob: None. S. A. Al-zubi: None. P. Boulle: None. S. Aebischer perone: None. L. Kiapi: None. A. H. Alani: None. H. Hering: None. M. Woodman: None.

Type 2 diabetes (T2D) prevalence increases unabated even as interventions focused on individuals at high risk can prevent T2D (1). Best approaches to identify individuals at high risk continue to be refined. Current risk assessment focuses on elevated glycemia, commonly estimated by fasting glucose (FG) and HbA1c levels, despite imperfect sensitivity and specificity (2). We previously showed that risk for T2D increases progressively as HbA1c increases, independently and in addition to increasing FG (3,4). As risk assessment for T2D depends on more than glycemia alone, simultaneous consideration of another physiological axis may improve biomarker-based diagnostic precision. Here, we test the hypothesis that simultaneous consideration of HbA1c and insulin resistance (IR), assessed with fasting insulin as HOMA of IR (HOMA-IR), can substantially improve risk assessment for T2D. We have previously detailed our statistical approach, IR and T2D diagnostic criteria, and particulars of the Framingham Heart Study (FHS) (3). Using the same FHS data and excluding those with T2D at baseline, we categorized individuals according to HbA1c

AIMS: To determine the association between 20-year trajectories in insulin resistance (IR) since young adulthood and appendicular lean mass (ALM) at middle-age in adults without diabetes. METHODS: A prospective cohort study was designed among young and middle-aged US men (n=925) and women (n=1,193). Fasting serum glucose and insulin were measured five times in 1985–2005. IR was determined using the homeostasis model assessment (HOMA). ALM was measured in 2005 and ALM adjusted for BMI (ALM/BMI) was the outcome. Sex-specific analyses were performed using latent class models and multivariable linear regressions. RESULTS: Three HOMA-IR trajectories were identified. Compared to the low-stable group, the adjusted ALM/BMI difference was −0.041 (95% CI: −0.060 to −0.022) and −0.114 (−0.141 to −0.086) in men, and −0.052 (−0.065 to −0.039) and −0.043 (−0.063 to −0.023) in women, respectively, for the medium-increase and high-increase group. Further adjusting for the treadmill test duration attenuated these estimates to −0.022 (−0.040 to −0.004) and −0.061 (−0.089 to −0.034) in men and −0.026 (−0.038 to −0.014) and −0.007 (−0.026 to 0.012) in women. CONCLUSIONS: Compared to the low-stable insulin resistance trajectory between early and middle adulthood, the high-increase insulin resistance trajectory was associated with lower ALM/BMI middle-aged men, but not women, without diabetes, after taking into account cardiorespiratory fitness.

Background: Obesity has been linked to severe clinical outcomes among people who are hospitalized with coronavirus disease 2019 (COVID-19). We tested the hypothesis that visceral adipose tissue (VAT) is associated with severe outcomes in patients hospitalized with COVID-19, independent of body mass index (BMI). Methods: We analyzed data from the Massachusetts General Hospital COVID-19 Data Registry, which included patients admitted with polymerase chain reaction–confirmed severe acute respiratory syndrome coronavirus 2 infection from March 11 to May 4, 2020. We used a validated, fully automated artificial intelligence (AI) algorithm to quantify VAT from computed tomography (CT) scans during or before the hospital admission. VAT quantification took an average of 2 ± 0.5 seconds per patient. We dichotomized VAT as high and low at a threshold of ≥100 cm² and used Kaplan-Meier curves and Cox proportional hazards regression to assess the relationship between VAT and death or intubation over 28 days, adjusting for age, sex, race, BMI, and diabetes status. Results: A total of 378 participants had CT imaging. Kaplan-Meier curves showed that participants with high VAT had a greater risk of the outcome compared with those with low VAT (P < .005), especially in those with BMI, National Institute of Diabetes and Digestive and Kidney Diseases (Grants T32DK007028 and R01DK085070), National Heart, Lung, and Blood Institute (Grant R01HL132786), National Institute of Allergy and Infectious Diseases (Grants R01AG062393 and K24AI141036), National Institute of General Medical Sciences (Grant R01GM127862)

Although less muscle mass is associated with greater diabetes prevalence in cross-sectional studies, prospective data in middle-aged Black and White adults are lacking. Middle age is a critical window as accelerated muscle loss is yet to occur, and preventing diabetes reduces lifelong morbidity and mortality. We hypothesized that lower appendicular lean mass adjusted for body mass index (ALM/BMI) is associated with higher incident diabetes in middle-aged Black and White adults in the Coronary Artery Risk Development in Young Adults (CARDIA) study. ALM/BMI was measured by dual x-ray energy absorptiometry (DXA) in 2005-06 among middle-aged US men (n=855) and women (n=1045) in CARDIA. Incident diabetes occurred if any of the following were met in 2010-11 or 2015-16 among persons without diabetes in 2005-06: fasting glucose ≥7 mmol/L (126 mg/dL), 2-hour glucose ≥11.1 mmol/L (200 mg/dL) on a 75-gram glucose tolerance test, HbA 1C ≥48 mmol/mol (6.5%), or use of glucose-lowering medications. We used logistic regression models with sex stratification given sex differences in ALM. In men, mean age was 45.0 ± 3.5 y, BMI 28.0 ± 4.3 kg/m 2 , and ALM/BMI 1.07 ± 0.14 m 2 . In women, mean age was 45.2 ± 3.6 years, BMI 28.4 ± 6.4 kg/m 2 , and ALM/BMI 0.73 ± 0.12 m 2 . Diabetes developed in 70 men (8.2%) and 72 women (6.9%). For each standard deviation increase in ALM/BMI (m 2 ), the risk of diabetes decreased by 22% in men and 29% in women (Table 1). After adjusting for age, race, smoking, education, physical activity, and waist circumference, the association of ALM/BMI with diabetes incidence was no longer significant. Associations were similar between race-ethnic groups. In conclusion, less relative skeletal muscle mass is associated with a greater risk of developing diabetes in middle-aged men and women over 10 years, which is largely explained by the relationship of ALM/BMI to other metabolic risk factors. Low skeletal muscle mass in middle age is a marker for greater diabetes risk and may be a target for preventative interventions.

Homeostatic control of blood glucose requires different physiological responses in the fasting and post-prandial states. We reasoned that glucose measurements under non-standardised conditions (random glucose; RG) may capture diverse glucoregulatory processes more effectively than previous genome-wide association studies (GWAS) of fasting glycaemia or after standardised glucose loads. Through GWAS meta-analysis of RG in 493,036 individuals without diabetes of diverse ethnicities we identified 128 associated loci represented by 162 distinct signals, including 14 with sex-dimorphic effects, 9 discovered through trans-ethnic analysis, and 70 novel signals for glycaemic traits. Novel RG loci were particularly enriched in expression in the ileum and colon, indicating a prominent role for the gastrointestinal tract in the control of blood glucose. Functional studies and molecular dynamics simulations of coding variants of GLP1R, a well-established type 2 diabetes treatment target, provided a genetic framework for optimal selection of GLP-1R agonist therapy. We also provided new evidence from Mendelian randomisation that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Thus, our approach based on RG GWAS provided wide-ranging insights into the biology of glucose regulation, diabetes complications and the potential for treatment stratification.

Background Epidemiological studies report associations of diverse cardiometabolic conditions including obesity with COVID-19 illness, but causality has not been established. We sought to evaluate the associations of 17 cardiometabolic traits with COVID-19 susceptibility and severity using 2-sample Mendelian randomization (MR) analyses. Methods and findings We selected genetic variants associated with each exposure, including body mass index (BMI), at p < 5 × 10−8 from genome-wide association studies (GWASs). We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. Susceptibility was defined as testing positive for COVID-19 and severity was defined as hospitalization with COVID-19 versus population controls (anyone not a case in contributing cohorts). We repeated the analysis for BMI with effect estimates from the UK Biobank and performed pairwise multivariable MR to estimate the direct effects and indirect effects of BMI through obesity-related cardiometabolic diseases. Using p < 0.05/34 tests = 0.0015 to declare statistical significance, we found a nonsignificant association of genetically higher BMI with testing positive for COVID-19 (14,134 COVID-19 cases/1,284,876 controls, p = 0.002; UK Biobank: odds ratio 1.06 [95% CI 1.02, 1.10] per kg/m2; p = 0.004]) and a statistically significant association with higher risk of COVID-19 hospitalization (6,406 hospitalized COVID-19 cases/902,088 controls, p = 4.3 × 10−5; UK Biobank: odds ratio 1.14 [95% CI 1.07, 1.21] per kg/m2, p = 2.1 × 10−5). The implied direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes, coronary artery disease, stroke, and chronic kidney disease. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Small study samples and weak genetic instruments could have limited the detection of modest associations, and pleiotropy may have biased effect estimates away from the null. Conclusions In this study, we found genetic evidence to support higher BMI as a causal risk factor for COVID-19 susceptibility and severity. These results raise the possibility that obesity could amplify COVID-19 disease burden independently or through its cardiometabolic consequences and suggest that targeting obesity may be a strategy to reduce the risk of severe COVID-19 outcomes., Aaron Leong and co-workers investigate causal risk factors for COVID-10 illness and severity., Author summary Why was this study done? Diverse cardiometabolic risk factors have been described in the literature to be associated with COVID-19 illness, but causality has not been established. Preventive strategies targeting cardiometabolic risk factors that are both causal and modifiable may reduce the risk of COVID-19 illness, whereas interventions targeting risk factors that are only correlated with the outcome may not. What did the researchers do and find? We used 2-sample Mendelian randomization analyses to test whether 17 cardiometabolic diseases and traits had a causal relationship with risk of COVID-19 illness. We found that higher body mass index was the only cardiometabolic risk factor among those we studied that was associated with a higher risk of hospitalization for COVID-19 compared to the general population. Obesity-related cardiometabolic diseases—type 2 diabetes, chronic kidney disease, stroke, and coronary heart disease—may be mediators of the relationship between body mass index and higher risk of hospitalization for COVID-19. What do these findings mean? Our results suggest that people with a higher body mass index have a higher risk for hospitalization for COVID-19. If other cardiometabolic risk factors have causal associations with COVID-19 illness, their effects are likely modest. We provide genetic evidence supporting body mass index as a causal risk factor for COVID-19 severity, raising the possibility that obesity could have amplified the COVID-19 pandemic, directly or through obesity-related cardiometabolic diseases.

Nonalcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver disease. Using a proxy NAFLD definition of chronic alanine aminotransferase elevation (cALT) without other liver diseases, we performed a trans-ancestry genome-wide association study in the Million Veteran Program including 90,408 cALT cases and 128,187 controls. In the Discovery stage, seventy-seven loci exceeded genome-wide significance – including 25 without prior NAFLD or ALT associations – with one additional locus identified in European-American-only and two in African-American-only analyses (P-8). External replication in cohorts with NAFLD defined by histology (7,397 cases, 56,785 controls) or liver fat extracted from radiologic imaging (n=44,289) validated 17 SNPs (P-4) of which 9 were novel (TRIB1, PPARG, MTTP, SERPINA1, FTO, IL1RN, COBLL1, APOH, and IFI30). Pleiotropy analysis showed that 61 of 77 trans-ancestry and all 17 validated SNPs were jointly associated with metabolic and/or inflammatory traits, revealing a complex model of genetic architecture. Our approach integrating cALT, histology and imaging reveals new insights into genetic liability to NAFLD.

Aims We aimed to characterize and illustrate the regional and state-level change in type 2 diabetes (T2D) prevalence in Mexico between 1990 and 2017. Methods We conducted an ecological and secondary analysis using data from the Global Burden of Disease study on T2D prevalence of the adult Mexican population. We estimated the absolute increase and annual growth rate of T2D prevalence between 1990 and 2017, stratified by age group and region. Results Nationally, between 1990 and 2017, the prevalence of T2D in Mexico increased from 9.5% to 14.3%. The highest increase in T2D prevalence was observed in the East and Southcentral regions, with the lowest absolute change in T2D prevalence observed in Northern states. The highest average annual growth rate in T2D prevalence was observed in Southern Mexico, in the three Southern states with the lowest human development index, and among individuals ages 15–49 years across all regions, compared to those 50 years and older. Conclusions The prevalence of T2D in Mexico has increased substantially over the past three decades, with a clear shift in T2D prevalence from Northern to Southern states and a faster increase occurring in Southern Mexico among younger adults and in areas with lower economic resources.

Objective To evaluate differences by race/ethnicity in clinical characteristics and outcomes among hospitalized patients with Covid-19 at Massachusetts General Hospital (MGH). Methods The MGH Covid-19 Registry includes confirmed SARS-CoV-2-infected patients hospitalized at MGH and is based on manual chart reviews and data extraction from electronic health records (EHRs). We evaluated differences between White/Non-Hispanic and Hispanic patients in demographics, complications and 14-day outcomes among the N = 866 patients hospitalized with Covid-19 from March 11, 2020—May 4, 2020. Results Overall, 43% of patients hospitalized with Covid-19 were women, median age was 60.4 [IQR = (48.2, 75)], 11.3% were Black/non-Hispanic and 35.2% were Hispanic. Hispanic patients, representing 35.2% of patients, were younger than White/non-Hispanic patients [median age 51y; IQR = (40.6, 61.6) versus 72y; (58.0, 81.7) (p Conclusions Hospitalized Hispanic patients were younger and had fewer comorbidities compared to White/non-Hispanic patients; despite comparable rates of ICU care or death, a greater proportion recovered. These results have implications for public health policy and the design and conduct of clinical trials.

Food insecurity and poor nutrition are prevalent in the United States and associated with chronic diseases. Understanding relationships among food insecurity, diet, and health care utilization can inform strategies to reduce health disparities.Our aim was to determine associations between food security status and inpatient and outpatient health care utilization and whether they differed by dietary quality in lower-income adults.This was a cross-sectional study of data from the 2009-2016 National Health and Nutrition Examination Survey.Participants were 13,956 lower-income (300% federal poverty level) adults 18 years and older in the United States.Self-reported health care utilization in the past 12 months included no usual source of care, any outpatient visit, any mental health service use, and any hospitalization.Multiple logistic regression was used to study the association between food insecurity and health care utilization. Analyses were stratified by diet-related comorbidities to account for potential confounding and mediation of health care utilization, and by dietary quality.In a sample of lower-income adults300% federal poverty level, 4,319 participants (27.4%) were food insecure, 2,208 (15.0%) were marginally food secure, and 7,429 (57.6%) were food secure. Food insecurity was associated with having no usual source of care (adjusted odds ratio [aOR] 1.30; 95% CI 1.11 to 1.52), any mental health service use (aOR 2.02; 95% CI 1.61 to 2.52), and any hospitalization (aOR 1.19; 95% CI 1.01 to 1.41). Food-insecure adults were more likely to report no outpatient visits if they had diet-related comorbidities (aOR 1.45; 95% CI 1.10 to 1.92) or the lowest dietary quality (aOR 1.53; 95% CI 1.06 to 2.23). Marginal food security was associated with having no usual source of care (aOR 1.22; 95% CI 1.04 to 1.44).Adults with food insecurity were more likely to be hospitalized, use mental health services, and have no usual source of care. Food-insecure participants with diet-related comorbidities or poor diet were less likely to have outpatient visits. Hospitalizations and mental health visits represent underused opportunities to identify and address food insecurity and dietary intake in lower-income patients.

Aims We aimed to evaluate the readiness and predictors of diabetes service capability at the level of primary care in Bangladesh as an illustrative instance of readiness for diabetes care in low- and middle-income countries (LMICs). Methods We used data from the 2014 Bangladesh Health Facility Survey (BHFS), a cross-sectional, nationally representative survey (n = 1596 health facilities). We constructed a diabetes-specific readiness index to assess diabetes service readiness in facilities with outpatient capability and used multivariable regression analysis to evaluate contextual predictors of diabetes service readiness. Results Three-hundred and forty-five facilities with outpatient and diabetes service capability were included. Mean readiness for diabetes service capability on a scale of 0–100 was 24.9 (95%CI: 20.8–28.9) and was lowest in rural settings, districts with high social deprivation, and public facilities, where diabetes diagnostic equipment and medications were largely unavailable. Facility type was the strongest, independent predictor of diabetes service readiness. Conclusions Diabetes service readiness in outpatient facilities in Bangladesh was low, particularly in public facilities, rural settings, and districts with high social deprivation. .These findings could inform policies aimed at improving diabetes care in areas of high unmet need and may serve as a model to assess diabetes service readiness in other LMICs.

OBJECTIVE Diabetes is an important risk factor for severe coronavirus disease 2019 (COVID-19), but little is known about the marginal effect of additional risk factors for severe COVID-19 among individuals with diabetes. We tested the hypothesis that sociodemographic, access to health care, and presentation to care characteristics among individuals with diabetes in Mexico confer an additional risk of hospitalization with COVID-19. RESEARCH DESIGN AND METHODS We conducted a cross-sectional study using public data from the General Directorate of Epidemiology of the Mexican Ministry of Health. We included individuals with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 between 1 March and 31 July 2020. The primary outcome was the predicted probability of hospitalization, inclusive of 8.5% of patients who required intensive care unit admission. RESULTS Among 373,963 adults with COVID-19, 16.1% (95% CI 16.0–16.3) self-reported diabetes. The predicted probability of hospitalization was 38.4% (37.6–39.2) for patients with diabetes only and 42.9% (42.2–43.7) for patients with diabetes and one or more comorbidities (obesity, hypertension, cardiovascular disease, and chronic kidney disease). High municipality-level of social deprivation and low state-level health care resources were associated with a 9.5% (6.3–12.7) and 17.5% (14.5–20.4) increased probability of hospitalization among patients with diabetes, respectively. In age-, sex-, and comorbidity-adjusted models, living in a context of high social vulnerability and low health care resources was associated with the highest predicted probability of hospitalization. CONCLUSIONS Social vulnerability contributes considerably to the probability of hospitalization among individuals with COVID-19 and diabetes with associated comorbidities. These findings can inform mitigation strategies for populations at the highest risk of severe COVID-19.

Glycaemic traits are used to diagnose and monitor type 2 diabetes, and cardiometabolic health. To date, most genetic studies of glycaemic traits have focused on individuals of European ancestry. Here, we aggregated genome-wide association studies in up to 281,416 individuals without diabetes (30% non-European ancestry) with fasting glucose, 2h-glucose post-challenge, glycated haemoglobin, and fasting insulin data. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P-8), 80% with no significant evidence of between-ancestry heterogeneity. Analyses restricted to European ancestry individuals with equivalent sample size would have led to 24 fewer new loci. Compared to single-ancestry, equivalent sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase understanding of diabetes pathophysiology by use of trans-ancestry studies for improved power and resolution.

BackgroundWe sought to develop an automatable score to predict hospitalization, critical illness, or death in patients at risk for COVID-19 presenting for urgent care during the Massachusetts outbreak.MethodsSingle-center study of adult outpatients seen in respiratory illness clinics (RICs) or the emergency department (ED), including development (n = 9381, March 7-May 2) and prospective (n = 2205, May 3-14) cohorts. Data was queried from Partners Enterprise Data Warehouse. Outcomes were hospitalization, critical illness or death within 7 days. We developed the COVID-19 Acuity Score (CoVA) using automatically extracted data from the electronic medical record and learning-to-rank ordinal logistic regression modeling. Calibration was assessed using predicted-to-observed ratio (E/O). Discrimination was assessed by C-statistics (AUC).ResultsIn the development cohort, 27.3%, 7.2%, and 1.1% of patients experienced hospitalization, critical illness, or death, respectively; and in the prospective cohort, 26.1%, 6.3%, and 0.5%. CoVA showed excellent performance in the development cohort (concurrent validation) for hospitalization (E/O: 1.00, AUC: 0.80); for critical illness (E/O: 1.00, AUC: 0.82); and for death (E/O: 1.00, AUC: 0.87). Performance in the prospective cohort (prospective validation) was similar for hospitalization (E/O: 1.01, AUC: 0.76); for critical illness (E/O 1.03, AUC: 0.79); and for death (E/O: 1.63, AUC=0.93). Among 30 predictors, the top five were age, diastolic blood pressure, blood oxygen saturation, COVID-19 testing status, and respiratory rate.ConclusionsCoVA is a prospectively validated automatable score to assessing risk for adverse outcomes related to COVID-19 infection in the outpatient setting.

Publisher's version (útgefin grein), Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p, WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C. The grant funding of WHI are R21 HL123677, R56 DK104806 and R01 MD012765 to NF. The FamHS was funded by R01HL118305 and R01HL117078 NHLBI grants, and 5R01DK07568102 and 5R01DK089256 NIDDK grant." and "The Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study was supported by the Intramural Research Program of the National Institute on Aging, National Institutes of Health (project # Z01-AG000513 and human subjects protocol number 09-AGN248). Support for GENOA was provided by the National Heart, Lung and Blood Institute (HL119443, HL087660, HL054464, HL054457, and HL054481) of the National Institutes of Health. Ruth loos is supported by the NIH (R01DK110113, U01HG007417, R01DK101855, R01DK107786). The Rotterdam Study GWAS datasets are supported by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012), the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), and the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) Netherlands Consortium for Healthy Aging (NCHA), project nr. 050-060-810. The ERF study as a part of EUROSPAN (European Special Populations Research Network) was supported by European Commission FP6 STRP grant number 018947 (LSHG-CT-2006- 01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007-2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme "Quality of Life and Management of the Living Resources" of 5th Framework Programme (no. QLG2-CT-2002- 01254). The ERF study was further supported by ENGAGE consortium and CMSB. Highthroughput analysis of the ERF data was supported by joint grant from Netherlands Organisation for Scientific Research and the Russian Foundation for Basic Research (NWORFBR 047.017.043).ERF was further supported by the ZonMw grant (project 91111025), and this work was partially supported by the National Heart, Lung and Blood Institute’s Framingham Heart Study (Contract No. N01-HC25195) and its contract with Affymetrix, Inc for genotyping services (Contract No. N02-HL-6- 4278). This study is also supported by National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) R01 DK078616 to Drs. Meigs, Dupuis and Florez, NIDDK K24 DK080140 to Dr. Meigs, and a Doris Duke Charitable Foundation Clinical Scientist Development Award to Dr. Florez. The HERITAGE Family Study was supported by National Heart, Lung, and Blood Institute grant HL-45670. The Women's Genome Health Study is supported by the National Heart, Lung, and Blood Instutute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913). Additional support for endpoint collection was provided by the National Heart, Lung, and Blood Institute under ARRA funding (HL099355). HyperGEN (Hypertension Genetic Epidemiology Network): The hypertension network is funded by cooperative agreements (U10) with NHLBI: HL54471, HL54472, HL54473, HL54495, HL54496, HL54497, HL54509, HL54515, and 2 R01 HL55673- 12. The AGES study has been funded by NIH contracts N01-AG-1-2100 and 271201200022C. Caroline Hayward is supported by an MRC University Unit Programme Grant MC_UU_00007/10 (QTL in Health and Disease)”and “Generation Scotland received core funding from the Chief Scientist Office of the Scottish Government Health Directorate CZD/16/6, the Scottish Funding Council HR03006 and the Wellcome Trust through a Strategic Award (reference 104036/Z/14/Z) for Stratifying Resilience and Depression Longitudinally (STRADL). Genotyping was funded by the UK's Medical Research Council. Jose C. Florez, NIDDK K24 DK110550 The MESA project is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1-TR-001881, and DK063491. Additionally, one or more authors are affiliated with the following commercial entities: Interleukin Genetics, GlaxoSmithKline, Daiichi-Sankyo, AstraZeneca, Data Tecnica International LLC, Illumina Inc., University of California Healthcare, Janssen Pharmaceuticals, Goldfinch Bio, and Novo Nordisk. Please see the Competing Interests Statement for additional details. The funders provided support in the form of salaries for authors but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.

Hypoglycemia is a preventable adverse effect of treatment in diabetes patients, but actionable pharmacogenetic evidence to minimize hypoglycemia risk is lacking. We used the MVP biospecimen and clinical biobank to perform a case/control GWAS of hypoglycemia in 96,406 diabetes patients receiving care in the U.S. Veterans Health Administration. Cases had an outpatient random plasma glucose (RPG) 1%. GWAS were conducted in 72,244 participants (22,045 cases) of European ancestry [EUR] and 24,162 (10,441 cases) of African ancestry [AFR]), adjusted for age at MVP enrollment, sex, and 10 genetic principal components. We identified a single locus associated with hypoglycemia in EUR individuals (rs1064173, HLA-DQB1 locus, odds ratio [OR] 1.15, p=5.6E-19, MAF 0.20) and in AFR individuals (rs12712928, SIX3 locus, OR 0.87, p=2.7E-8, MAF 0.17). In a phenomewide association study (PheWAS) in MVP EUR diabetes patients, rs1064173 was associated with type 1 diabetes (T1D, OR 1.41, p=7.8E-25) and diabetes complications (retinopathy, OR 1.24, p=9E-24; neuropathy, OR 1.16, p=1.3E-5). To address the known association of the HLA locus with T1D, we performed a sensitivity analysis excluding patients with any use of T1D diagnosis codes. In this sample enriched for type 2 diabetes, rs1064173 remained nominally associated with hypoglycemia (OR 1.23, p=0.02) and retinopathy (OR 1.10, p=0.003). Rs12712928 - previously associated with glucose and hemoglobin A1c in an East Asian sample - was not associated with any diagnoses in a PheWAS of MVP AFR diabetes patients. In conclusion, a GWAS of hypoglycemia in a clinical biobank found ancestry-specific genetic associations that may have treatment implications. Disclosure S. Raghavan: None. Z. Wang: None. A.M. Hung: None. B.R. Charest: None. L. Costa: None. E.M. Litkowski: None. A. Leong: None. J.B. Meigs: Consultant; Self; Quest Diagnostics. P.W. Wilson: None. P. Reaven: Consultant; Self; Boston Heart Diagnostics, Intercept Pharmaceuticals, Inc. Research Support; Self; Bristol-Myers Squibb, Lysulin. M.K. Rhee: Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc. Y.V. Sun: None. L.S. Phillips: Research Support; Self; AbbVie Inc., Diasome Pharmaceuticals, Inc., Eli Lilly and Company, GlaxoSmithKline plc., Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Pfizer Inc., Sanofi-Aventis. Other Relationship; Self; Diasyst, Janssen Pharmaceuticals, Inc. Funding U.S. Department of Veterans Affairs (I01-CX001737, IK2-CX001907-01)

Patients with type 2 diabetes (T2D) are at two-fold increased risk of cardiovascular disease (CVD). CVD is the leading cause of T2D morbidity and mortality. The aim of this study was to identify genetic risk factors associated with incident CVD in patients with T2D. We performed survival genome-wide association study (GWAS) with patients with T2D in the UK Biobank (UKBB), Partners HealthCare Biobank (PBB), and Korean Genome and Epidemiology (KoGES) studies. The primary outcome of the study was a composite of myocardial infarction and stroke that occurred at least one year after the diagnosis of T2D. We conducted survival GWAS using ’GWASTools’ R package adjusting for age, and sex. The results of the three cohorts were meta-analyzed using inverse variance weighted method. A total of 19,121 participants were included in the analyses (15,643 from UKBB, 1,161 from PBB and 2,317 from KoGES). The incidence rate of CVD was higher in the hospital-based study of PBB (33.5%) compared to population-based studies of UKBB (9.5%), and KoGES (8.0%). Although there was no genetic association reaching genome-wide significance, there were four genomic loci that had suggestive association evidence for incident CVD with P In summary, we have implemented survival GWAS analysis to investigate genetic risk factors for incident CVD in patients with T2D. However, further increase in sample size is required to identify molecular features leading to increased CVD risk among individuals with T2D. Disclosure S. Kwak: None. J.M. Mercader: None. A. Leong: None. B. Porneala: None. P. Wu: None. J.B. Cole: None. J. Merino: None. K. Park: None. N.H. Cho: None. J. Dupuis: Consultant; Self; Merck Sharp & Dohme Corp. J.C. Florez: Advisory Panel; Self; Doris Duke Charitable Foundation. Other Relationship; Self; Novo Nordisk Inc., Park Street School. J.B. Meigs: Consultant; Self; Quest Diagnostics.

Polygenic scores constructed by the aggregation of effect sizes of associated genetic variants have been shown to predict type 2 diabetes (T2D). Polygenic scores can be defined as “restricted-to-significant polygenic scores” (rsPS), and “globally expanded polygenic scores” (gePS), which can include millions of variants beyond those that are genome-wide significant. Most polygenic scores have been generated based on genome-wide association studies (GWAS) conducted predominantly in participants of European ancestry (EU); how these polygenic scores perform in non-European individuals in the healthcare system has not been thoroughly evaluated. We applied the rsPS and gePS for T2D in 30,240 EU participants, 3,029 Latinos (LA), and 2,201 African Americans (AA) from the Partners HealthCare Biobank, which maintains blood and DNA samples from patients seen at Partners HealthCare-affiliated hospitals in Boston. We compared rsPS based on the DIAMANTE consortium meta-analysis, with 398 variants (rsPS_398), rsPS based on the latest Million Veterans Program meta-analysis, with 682 variants (rsPS_682), and a gePS based on ldpred, including 6.9M variants adjusted for their effects based on linkage disequilibrium. rsPS_682 was most strongly associated with T2D in all ancestries (OR per SD in EU=1.73 p=7×10-142, OR per SD in LA =1.88, p=7×10-19, OR per SD in AA =1.47, p=1×10-8 compared to the other polygenic scores. We observed that rsPS_682 and the gePS provided both complementary information, and that combining them into the model improved the prediction in all ancestries, with 16%, 22%, and 16% increase in accuracy in EU, LA, and AA, respectively. We show the advantage of combining rsPS and gePS to improve prediction of T2D in multi-ethnic populations within a healthcare system. The results suggest that larger and multi-ethnic T2D GWAS are needed to avoid major health disparities. Disclosure J.M. Mercader: None. J.C. Florez: Advisory Panel; Self; Doris Duke Charitable Foundation. Other Relationship; Self; Novo Nordisk Inc., Park Street School. A. Leong: None. V. Kaur: None. M. Udler: None. J.B. Meigs: Consultant; Self; Quest Diagnostics. B. Porneala: None. Funding American Diabetes Association (1-19-ICTS-068 to J.M.M.)

Background and Objective: CHIP is the aging-related accumulation of genetic mutations in the hematopoiesis-associated genes of stem cells. CHIP was recently associated with total mortality and atherosclerotic cardiovascular disease. We tested the hypothesis that CHIP is associated with adverse glycemic traits and incident T2D risk. Methods: This study includes a subset of n=9,704 individuals in the NHLBI Trans-omics for Precision Medicine (TOPMed) project from the Framingham Heart Study (FHS), Jackson Heart Study (JHS), Multi-Ethnic Study of Atherosclerosis (MESA) and Women’s Health Initiative (WHI). We analyzed individuals without a history of T2D, cancer, or cardiovascular disease, and collected blood for fasting glycemic traits and CHIP carrier status. CHIP was recently determined from blood DNA-derived whole genome sequencing using the CATK MuTECT2 somatic variant caller in pre-specified leukemogenic driver mutations in candidate clonal expansion genes. We are conducting multivariable linear models examining both cross-sectional associations of CHIP with glycemic traits and survival models for baseline CHIP with incident T2D, adjusting for age, sex, body mass index, smoking, cohort, and family history of diabetes. Results: Mean (SD) age was FHS = 50 (14), JHS = 55 (13), MESA = 60 (10), and WHI = 66 (7) years. We identified n=460 (4.7%) as CHIP carriers. The most common variant was located in DNMT3A gene (60% of carriers). Among CHIP carriers, the prevalence of having CHIP present in 1 of the 4 genes previously implicated in atherosclerotic heart disease (DNMT3A, TET2, ASXL1, JAK2; Jaiswal, et al, NEJM 2017) was lowest in FHS (75%) and highest in JHS (96%). Results for CHIP in relation to glycemic traits and incident T2D (∼1,500 cases) will be presented in detail. We will additionally present the associations for gene-specific CHIP mutations. Conclusions: These cutting-edge TOPMed data will elucidate the role of CHIP, a novel aging biomarker, in relation to T2D risk. Disclosure D.K. Tobias: None. S. Raghavan: None. A. Bick: None. L. Raffield: None. P. Wu: None. D.A. DiCorpo: None. J. Dupuis: Consultant; Self; Merck Sharp & Dohme Corp. L. Lange: None. J.I. Rotter: None. C.L. Kooperberg: None. J.B. Meigs: Consultant; Self; Quest Diagnostics. J.E. Manson: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (U01DK078616 to J.B.M., J.D., D.A.D., P.W.), (U01DK105554 to J.D., D.A.D.)

OBJECTIVE Diabetes is a rapidly growing health problem in low- and middle-income countries (LMICs), but empirical data on its prevalence and relationship to socioeconomic status are scarce. We estimated diabetes prevalence and the subset with undiagnosed diabetes in 29 LMICs and evaluated the relationship of education, household wealth, and BMI with diabetes risk. RESEARCH DESIGN AND METHODS We pooled individual-level data from 29 nationally representative surveys conducted between 2008 and 2016, totaling 588,574 participants aged ≥25 years. Diabetes prevalence and the subset with undiagnosed diabetes was calculated overall and by country, World Bank income group (WBIG), and geographic region. Multivariable Poisson regression models were used to estimate relative risk (RR). RESULTS Overall, prevalence of diabetes in 29 LMICs was 7.5% (95% CI 7.1–8.0) and of undiagnosed diabetes 4.9% (4.6–5.3). Diabetes prevalence increased with increasing WBIG: countries with low-income economies (LICs) 6.7% (5.5–8.1), lower-middle-income economies (LMIs) 7.1% (6.6–7.6), and upper-middle-income economies (UMIs) 8.2% (7.5–9.0). Compared with no formal education, greater educational attainment was associated with an increased risk of diabetes across WBIGs, after adjusting for BMI (LICs RR 1.47 [95% CI 1.22–1.78], LMIs 1.14 [1.06–1.23], and UMIs 1.28 [1.02–1.61]). CONCLUSIONS Among 29 LMICs, diabetes prevalence was substantial and increased with increasing WBIG. In contrast to the association seen in high-income countries, diabetes risk was highest among those with greater educational attainment, independent of BMI. LMICs included in this analysis may be at an advanced stage in the nutrition transition but with no reversal in the socioeconomic gradient of diabetes risk.

BACKGROUND: Women with gestational glucose intolerance, defined as an abnormal initial gestational diabetes screening test, are at risk for adverse pregnancy outcomes even if they do not have gestational diabetes. We previously defined gestational diabetes physiologic subtypes based on the primary underlying physiology leading to hyperglycemia and found that women with different subtypes had differential risk of adverse outcomes. Physiologic subclassification has not yet been applied to women with gestational glucose intolerance. OBJECTIVE: We defined gestational glucose intolerance physiologic subtypes based on the presence of insulin resistance, insulin deficiency, or mixed pathophysiology, and aimed to determine if these subtypes are at differential risk for adverse outcomes. We hypothesized that women with the insulin resistant subtype of gestational glucose intolerance would have the greatest risk of adverse pregnancy outcomes. STUDY DESIGN: In a hospital-based cohort study, we studied women with gestational glucose intolerance (glucose loading test 1-hour glucose ≥140 mg/dL, N=236) and normal glucose tolerance (glucose loading test 1-hour glucose

Background:Cardiovascular disease (CVD) risk is elevated in HIV-infected individuals, with contributions from both traditional and nontraditional risk factors. The accuracy of established CVD risk prediction functions in HIV is uncertain. We sought to assess the performance of 3 established CVD risk prediction functions in a longitudinal cohort of HIV-infected men.Methods:The FHS (Framingham Heart Study) functions for hard coronary heart disease (FHS CHD) and atherosclerotic CVD (FHS ASCVD) and the American College of Cardiology/American Heart Association ASCVD function were applied to the Partners HIV cohort. Risk scores were calculated between January 1, 2006, and December 31, 2008. Outcomes included CHD (myocardial infarction or coronary death) for the FHS CHD function and ASCVD (myocardial infarction, stroke, or coronary death) for the FHS ASCVD and American College of Cardiology/American Heart Association ASCVD functions. We investigated the accuracy of CVD risk prediction for each function when applied to the HIV cohort using comparison of Cox regression coefficients, discrimination, and calibration.Results:The HIV cohort was comprised of 1272 men followed for a median of 4.4 years. There were 78 (6.1%) ASCVD events; the 5-year incidence rate was 16.4 per 1000 person-years. Discrimination was moderate to poor as indicated by the lowcstatistic (0.68 for FHS CHD, 0.65 for American College of Cardiology/American Heart Association ASCVD, and 0.67 for FHS ASCVD). Observed CVD risk exceeded the predicted risk for each of the functions in most deciles of predicted risk. Calibration, or goodness of fit of the models, was consistently poor, with significant χ2Pvalues for all functions. Recalibration did not significantly improve model fit.Conclusions:Cardiovascular risk prediction functions developed for use in the general population are inaccurate in HIV infection and systematically underestimate risk in a cohort of HIV-infected men. Development of tailored CVD risk prediction functions incorporating traditional CVD risk factors and HIV-specific factors is likely to result in more accurate risk estimation to guide preventative CVD care.

Objective To determine if the greater risk of ischemic stroke observed in women living with HIV infection (WLWH) compared with HIV-uninfected women persists after accounting for both traditional and sex-specific stroke risk factors. Methods We performed an observational cohort study of WLWH (n = 1214) and demographics-matched HIV-uninfected women (n = 12 041) seen between 1996 and 2011 at two tertiary care hospitals in Boston. We used Cox proportional hazards regression analyses to model time to ischemic stroke, adjusting first for demographics and traditional stroke risk factors and then for sex-specific stroke risk factors, including menopause and estrogen use. We also constructed demographics-adjusted Cox models to identify HIV-related risk factors associated with ischemic stroke among WLWH. Results The incidence of ischemic stroke was higher among WLWH compared with HIV-uninfected women [incidence rate ratio 2.39, 95% confidence interval (CI) 1.62-3.43]. After adjusting for demographics and traditional stroke risk factors, HIV infection was associated with almost twice the risk of ischemic stroke (hazard ratio 1.93, 95% CI 1.31-2.85). The association of HIV with ischemic stroke persisted after inclusion of sex-specific stroke risk factors in the model (hazard ratio 1.89, 95% CI 1.28-2.81). Among WLWH, longer duration of antiretroviral therapy was associated with lower ischemic stroke risk (hazard ratio 0.86 per year, 95% CI 0.76-0.96). Conclusion The increased risk of ischemic stroke among WLWH compared with HIV-uninfected women persisted after adjusting for both traditional and sex-specific stroke risk factors. Further investigation into the mechanisms of elevated stroke risk among WLWH, including immunologic factors, will be key for developing targeted preventive strategies for this at-risk population.

Objective Studies have indicated that both increased and suppressed immune system activity may affect depression severity. We tested the hypothesis that higher or lower white blood cell (WBC) count at first depression diagnosis is associated with an increased risk of hospitalization with depression. Methods We identified individuals in a hospital-affiliated primary care network with a WBC count at the first-time depression diagnosis in 2006–2011. Outcome was subsequent hospitalization with depression. We followed individuals for three years and performed Cox regression analyses adjusted for age, gender, race, Charlson comorbidity score, obesity, and smoking. Significance was set at p Results We identified 2400 individuals with a mean WBC count of 7.1 × 109/L at first-time depression diagnosis, of which 55 were hospitalized with depression. Compared to WBC between 4.5–6 × 109/L, individuals with WBC of 1–4.5 × 109/L were associated with a hazard rate (HR) of 3.56 (95%CI = 1.02-12.39; p = 0.046) for the risk of hospitalization with depression. Individuals with WBC of 6–10 × 109/L were associated with a HR of 2.62 (95%CI = 1.02-6.71, p = 0.044) whereas no association was found among individuals with WBC of 10–25 × 109/L (HR = 1.81; 95%CI = 0.54-6.07). Conclusions Our results are in line with previous clinical findings showing that the severity of depression differs based on WBC counts, particularly concerning low WBC levels. Future large clinical trials need to investigate whether WBC may help in prediction of antidepressant treatment outcome.

Aims We sought to investigate whether individuals with diabetes have a higher likelihood of testing positive for SARS-CoV-2, as a proxy for infection risk, than individuals without diabetes. Methods We conducted a cross-sectional study of publicly available data among a Mexican population, totaling 2,314,022 adults ≥ 18 years who underwent SARS-CoV-2 testing between March 1 and December 20, 2020. We used 1:1 nearest neighborhood propensity score matching by diabetes status to account for confounding among those with and without diabetes. Results In the overall study population, 1,057,779 (45.7%) individuals tested positive for SARS-CoV-2 and 270,486 (11.7%) self-reported diabetes. After propensity score matching, patient characteristics were well-balanced, with 150,487 patients in the diabetes group (mean [SD] age 55.9 [12.7] years; 51.3% women) and 150,487 patients in the no diabetes group (55.5 [13.3] years; 50.3% women). The strictest matching algorithm (1:1 nearest neighbor) showed that compared to individuals without diabetes, having diabetes was associated with 9.0% higher odds of having a positive SARS-CoV-2 test (OR 1.09 [95% CI: 1.08–1.10]). Conclusions Presence of diabetes was associated with higher odds of testing positive for SARS-CoV-2, which could have important implications for risk mitigation efforts for people with diabetes at risk of SARS-CoV-2 infection.

Background: Inconsistent evidence describes the association between dietary intake of dairy and milk-based products and type 2 diabetes (T2D) risk.Objective: Our objective was to assess associations between consumption of milk-based products, incident prediabetes, and progression to T2D in the Framingham Heart Study Offspring Cohort.Methods: Total dairy and milk-based product consumption was assessed by ≤4 food-frequency questionnaires across a mean of 12 y of follow-up in 2809 participants [mean ± SD age: 54.0 ± 9.7 y; body mass index (in kg/m2): 27.1 ± 4.7; 54% female]. Prediabetes was defined as the first occurrence of fasting plasma glucose ≥5.6 to

Background In the United States, diabetes mellitus (DM) is among the most common chronic diseases, with approximately 34.2 million people affected. DM has also emerged as a commonly reported risk factor among people hospitalized with coronavirus disease 2019 (COVID-19). In this study, we sought to evaluate whether people with DM who are hospitalized with COVID-19 were more likely to experience poor early outcomes and whether this association remained after adjustment for obesity status. Methods We analyzed data from the Massachusetts General Hospital (MGH) COVID-19 Data Registry. The sample included 450 people with PCR-confirmed SARS-CoV-2 infection who were hospitalized at MGH between March 11, 2020 and April 30, 2020. The primary outcomes were (1) admission to the intensive care unit (ICU) and (2) need for mechanical ventilation or death, both within 14 days of presentation to care. Data were obtained by manual chart review and via an EMR-associated database. Logistic regression was used to evaluate the relationship between diabetes and these outcomes. All models were adjusted for age, sex, race, BMI category and key comorbidities. Results In this study, 178 (39.6%) of 450 participants had DM and 346 (76.9%) were overweight or obese. People with DM were on average older and had a higher BMI than those without DM. A higher percentage of patients with DM were admitted to the ICU (42.1% vs 29.8%, p=0.007) and required mechanical ventilation or died (46.6% vs 27.7%, p< 0.001), compared with patients without DM (Figure 1). In adjusted models, DM was associated with a greater odds of ICU admission (aOR: 1.58 [95% CI: 1.01–2.46]) and mechanical ventilation or death (2.15 [1.38–3.34). Obesity was associated with a greater odds of ICU admission (2.15 [1.20–3.86]) but not with mechanical ventilation or death (1.52 [0.87–2.67]). Table 1 provides the model results in full. Figure 1. ICU Admission and mechanical ventilation or death within 14-days by diabetes status among 450 people hospitalized with COVID-19 Conclusion Diabetes was associated with poor outcomes within 14-days of presentation to care for COVID-19. These findings remained after adjustment for obesity. Our findings can help guide risk mitigation efforts and patient-centered care decision making for people with DM and obesity, particularly in areas of the US that have a high prevalence of DM and obesity and are in early phases of the SARS-CoV-2 outbreak. Disclosures Sara Jane Cromer, MD, Depuy-Synthes (a Johnson & Johnson company) (Employee) James Meigs, MD, Quest Diagnostics (Other Financial or Material Support, Academic Associate) Deborah Wexler, MD, Novo Nordisk (Other Financial or Material Support, Data Monitoring Committee)

We investigated type 2 diabetes (T2D) genetic susceptibility in a multi-ethnic meta-analysis of 228,499 cases and 1,178,783 controls in the Million Veteran Program (MVP) and other biobanks. We identified 558 autosomal and 10 X-chromosome T2D-associated variants, of which 286 autosomal and 7 X-chromosome variants were previously unreported. Ancestry-specific analyses identified 25 additional novel T2D-susceptibility variants. Transcriptome-wide association analysis detected 3,568 T2D-associations with T2D-colocalized genetically predicted gene expression of 804 genes in 52 tissues, of which 687 are novel. Fifty-four of these genes are known to interact with FDA-approved drugs and chemical compounds. T2D polygenic risk score was strongly associated with increased the risk of T2D-related retinopathy, and additionally showed evidence for association with chronic kidney disease (CKD), neuropathy, and peripheral artery disease (PAD). We investigated the genetic etiology of T2D-related vascular outcomes in the MVP and observed statistical SNP-T2D interactions at 13 variants, including 3 for coronary heart disease, 1 for PAD, 2 for stroke, 4 for retinopathy, 2 for CKD, and 1 for neuropathy. Our findings may identify potential novel therapeutic targets for T2D and genomic pathways that link T2D and its vascular outcomes.

Background & aimsGiven ongoing challenges in non-invasive non-alcoholic liver disease (NAFLD) diagnosis, we sought to validate an ALT-based NAFLD phenotype using measures readily available in electronic health records (EHRs) and population-based studies by leveraging the clinical and genetic data in the Million Veteran Program (MVP), a multi-ethnic mega-biobank of US Veterans.MethodsMVP participants with alanine aminotransferases (ALT) >40 units/L for men and >30 units/L for women without other causes of liver disease were compared to controls with normal ALT. Genetic variants spanning eight NAFLD risk or ALT-associated loci (LYPLAL1, GCKR, HSD17B13, TRIB1, PPP1R3B, ERLIN1, TM6SF2, PNPLA3) were tested for NAFLD associations with sensitivity analyses adjusting for metabolic risk factors and alcohol consumption. A manual EHR review assessed performance characteristics of the NAFLD phenotype with imaging and biopsy data as gold standards. Genetic associations with advanced fibrosis were explored using FIB4, NAFLD Fibrosis Score and platelet counts.ResultsAmong 322,259 MVP participants, 19% met non-invasive criteria for NAFLD. Trans-ethnic meta-analysis replicated associations with previously reported genetic variants in all but LYPLAL1 and GCKR loci (PConclusionsWe validate a simple, non-invasive ALT-based NAFLD phenotype using EHR data by leveraging previously established NAFLD risk-associated genetic polymorphisms.

PURPOSE OF REVIEW: Genome-wide association studies have delineated the genetic architecture of type 2 diabetes. While functional studies to identify target transcripts are ongoing, new genetic knowledge can be translated directly to health applications. The review covers several translation directions but focuses on genomic polygenic scores for screening and prevention. RECENT FINDINGS: Over 400 genomic variants associated with T2D and its related quantitative traits are now known. Genetic scores comprising dozens to millions of associated variants can predict incident T2D. However, measurement of body mass index is more efficient than genetic scores to detect T2D risk groups, and knowledge of T2D genetic risk alone seems insufficient to improve health. Genetically determined metabolic sub-phenotypes can be identified by clustering variants associated with physiological axes like insulin resistance. Genetic sub-phenotyping may be a way forward to identify specific individual phenotypes for prevention and treatment. SUMMARY: Genomic polygenic scores for T2D can predict incident diabetes but may not be useful to improve health overall. Genetic detection of T2D sub-phenotypes could be useful to personalize screening and care.

Type 2 diabetes (T2D) affects the health of millions of people worldwide. The identification of genetic determinants associated with changes in glycemia over time might illuminate biological features that precede the development of T2D. Here we conducted a genome-wide association study of longitudinal fasting glucose changes in up to 13,807 non-diabetic individuals of European descent from nine cohorts. Fasting glucose change over time was defined as the slope of the line defined by multiple fasting glucose measurements obtained over up to 14 years of observation. We tested for associations of genetic variants with inverse-normal transformed fasting glucose change over time adjusting for age at baseline, sex, and principal components of genetic variation. We found no genome-wide significant association (P −8) with fasting glucose change over time. Seven loci previously associated with T2D, fasting glucose or HbA1c were nominally (P

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, I 2 =7.1%, τ 2 =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, I 2 =18.0%, τ 2 =0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I 2 =58.8%, τ 2 =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, I 2 =25.9%, τ 2 =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.

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in patients 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/FN3KRP in Europeans and G6PD in African-Americans and Hispanics) and discovered a new African-ancestry specific low-frequency variant (rs1039215 in HBG2/HBE1, minor allele frequency (MAF)=0.03). The most associated G6PD variant (p.Val98Met, rs1050828-T, 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 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.

Background Individuals with human immunodeficiency virus (HIV) face elevated cardiovascular disease (CVD) risk. There are limited data regarding the application of the American College of Cardiology/American Heart Association (ACC/AHA) cholesterol guidelines in HIV compared with non-HIV patients. Methods Human immunodeficiency virus-infected and demographically similar control patients were assessed for statin recommendation status by ACC/AHA and the National Cholesterol Education Program Adult Treatment Program III (ATPIII), indication for statin recommendation, actual statin prescription, and CVD event. Outcomes were atherosclerotic CVD for ACC/AHA and coronary heart disease for ATPIII. Results In a clinical care cohort of 1394 patients infected with HIV, 38.6% (538 of 1394) of patients were recommended for statin therapy by the ACC/AHA guidelines compared with 20.1% (280 of 1394) by the ATPIII guidelines. Of those recommended for statin therapy, actual statin prescription rates were 42.8% (230 of 538) for ACC/AHA and 66.4% (186 of 280) for ATPIII. Among patients infected with HIV with an incident CVD event during follow-up, statin therapy was recommended for 59.2% (42 of 71) of patients by ACC/AHA and 35.2% (25 of 71) by ATPIII, versus 71.6% (141 of 197) by ACC/AHA and 43.1% (85 of 197) by ATPIII in the control group. Conclusions In an HIV clinical care cohort, the ACC/AHA cholesterol guidelines recommend a higher proportion of patients for statin therapy and identify an increased proportion of patients with a CVD event compared with ATPIII. However, 40% of patients with a CVD event would not have been recommended for statin therapy by ACC/AHA, compared with 29% for controls. This gap in identification of patients infected with HIV at high CVD risk underscores the need for HIV-specific cardiovascular prevention strategies.