Frank B. Hu

Bio: Frank B. Hu is an academic researcher from Harvard University. The author has contributed to research in topics: Type 2 diabetes & Diabetes mellitus. The author has an hindex of 250, co-authored 1675 publications receiving 253464 citations. Previous affiliations of Frank B. Hu include Southwest University & Brigham and Women's Hospital.

Impaired Ghrelin Response after High-Fat Meals Is Associated with Decreased Satiety in Obese and Lean Chinese Young Adults

Abstract: Ghrelin and peptide tyrosine tyrosine (PYY) are known to affect appetite and body weight, but the acute effects of fat-rich and carbohydrate-rich meals on plasma ghrelin, PYY response, and appetite remain unclear. We hypothesized that obese individuals had impaired postprandial ghrelin and PYY response based on macronutrient content of meals, affecting appetite and energy intake. We conducted a randomized crossover trail comparing fasting ghrelin and PYY concentrations, postprandial ghrelin and PYY responses, and subjective appetite in 15 obese and 12 lean Chinese young adults after they consumed isocaloric high-carbohydrate [HC; 88% energy carbohydrate, 4% energy fat, 8% energy protein] and high-fat (HF; 25% energy carbohydrate, 71 % energy fat, 4% energy protein) meals. Ghrelin concentrations over time differed between HC and HF meals (P< 0.01) via repeated measures of ANOVA, with lower postprandial ghrelin suppression after HF meals, especially among obese participants. PYY response differed between meals among lean participants, with a delayed and higher postprandial PYY peak after the HF meal (P < 0.01); however, PYY response did not differ among obese participants. The incremental area under the curve of PYY was higher in lean than in obese participants after the HF meal (P < 0.01). These results suggest that impaired ghrelin response after HF meals may contribute to reduced satiety and overeating, especially among obese individuals. Whether an attenuated response of PYY in obese participants after a HF meal bears any physiological consequences warrants further study.

Joint role of non-HDL cholesterol and glycated haemoglobin in predicting future coronary heart disease events among women with type 2 diabetes.

Abstract: Aims/hypothesis Non-HDL cholesterol (the sum of LDL, VLDL and IDL cholesterol) is considered to be particularly valuable in the management of dyslipidaemia in type 2 diabetes. However, it remains uncertain whether the association between non-HDL cholesterol and cardiovascular risk in type 2 diabetes depends on the status of hyperglycaemia. We aimed to determine whether non-HDL cholesterol predicts CHD events among diabetic women independently of currently established risk factors and the status of glycaemic control.

Metabolic Profiling of Diabetes: From Black-Box Epidemiology to Systems Epidemiology

Abstract: Type 2 diabetes (T2D)2 is a heterogeneous condition that is characterized by increased insulin resistance and impaired insulin secretion. A progressive disorder with an insidious onset, T2D typically progresses from an early asymptomatic insulin resistance state to mild glucose intolerance and eventually to frank T2D that requires pharmacologic interventions. Whether insulin resistance or impaired insulin secretion is the primary defect in the pathogenesis of T2D remains a matter of debate. Interestingly, most genetic variants identified from recent genome-wide association studies are related to decreased β-cell function or impaired insulin secretion, which implicates a key role for β-cell dysfunction in the development of T2D. Still, obesity, with its fundamental influence on insulin resistance, is the single most important risk factor for T2D. Although T2D is largely predictable through anthropometric, lifestyle, and clinical factors and is preventable through diet and exercise, the metabolic pathways underlying the progression from normal glycemia to a prediabetes state and later to T2D are not completely understood. Classic epidemiology typically relates lifestyle and environmental exposures to chronic disease end points, such as T2D. This approach (sometimes referred to as “black-box epidemiology”) has identified many important lifestyle and environmental risk factors for chronic diseases, but it often does not illuminate biological mechanisms that underlie observed associations. Recent advances in “omics” technology, however, have enabled epidemiologists to incorporate novel biomarkers at multiple levels into human observational studies, with the potential to shift the research paradigm from the traditional black-box strategy to a systems approach (1, 2). This new model integrates a wide range of information—genetic predisposition (genome), epigenetic changes (epigenome), the expression of genes (transcriptome), proteins (proteome), metabolites (metabolome), and gut microbiota (microbiome)—into population-based studies to improve our understanding of the biological mechanisms that underlie disease pathophysiology in humans. Systems epidemiology is at the intersection of …

Interleukin-6 Receptor Gene Variations, Plasma Interleukin-6 Levels, and Type 2 Diabetes in U.S. Women

Abstract: OBJECTIVE— To examine the associations between common variations in the IL6R gene and circulating interleukin (IL)-6 levels and diabetes risk. RESEARCH DESIGN AND METHODS— We determined 10 linkage disequilibrium (LD)-tagging single nucleotide polymorphisms (SNPs) (SNP1 to SNP10) for the IL6R gene in a nested case-control study of 672 diabetic and 1,058 healthy European Caucasian women (IL-6 levels were measured in a subgroup of 1,348 women). RESULTS— In both control and diabetic patients, polymorphisms within an LD block spanning ∼42 kb were significantly associated with plasma IL-6 levels. A missense variant SNP7 in exon 9 (rs8192284, Asp358Ala) showed the strongest association ( P = 0.0005 in control and P = 0.004 in case subjects). The corresponding false-discovery rates, which accounts for multiple testing, were 0.008 and 0.02, respectively. We inferred five common haplotypes to capture 94% allele variance of the LD block using SNP5, -7, -8, -9, and -10. Compared with the most common haplotype 12111 (one codes the common and two codes the minor alleles), haplotypes 11211 [difference in log(IL-6) = −0.11 (95% CI −0.23 to −0.01); P = 0.01] and 21122 (−0.15 [−0.27 to −0.03]; P = 0.01) were associated with significantly lower IL-6 levels (global test, P = 0.01). However, IL6R genotypes were not significantly associated with the risk of type 2 diabetes. CONCLUSIONS— IL6R genetic variations, especially SNP7 (rs8192284, Asp358Ala), were significantly associated with plasma IL-6 levels but not with diabetes risk in women. The strong associations between IL6R genetic variability and IL-6 concentrations deserve further investigation.

Rare coding variants and X-linked loci associated with age at menarche

Abstract: More than 100 loci have been identified for age at menarche by genome-wide association studies; however, collectively these explain only similar to 3% of the trait variance. Here we test two overlooked sources of variation in 192,974 European ancestry women: low-frequency proteincoding variants and X-chromosome variants. Five missense/nonsense variants (in ALMS1/LAMB2/TNRC6A/TACR3/PRKAG1) are associated with age at menarche (minor allele frequencies 0.08-4.6%; effect sizes 0.08-1.25 years per allele; P<5 x 10(-8)). In addition, we identify common X-chromosome loci at IGSF1 (rs762080, P = 9.4 x 10(-13)) and FAAH2 (rs5914101, P = 4.9 x 10(-10)). Highlighted genes implicate cellular energy homeostasis, post-transcriptional gene silencing and fatty-acid amide signalling. A frequently reported mutation in TACR3 for idiopathic hypogonatrophic hypogonadism (p.W275X) is associated with 1.25-year-later menarche (P = 2.8 x 10(-11)), illustrating the utility of population studies to estimate the penetrance of reportedly pathogenic mutations. Collectively, these novel variants explain similar to 0.5% variance, indicating that these overlooked sources of variation do not substantially explain the 'missing heritability' of this complex trait.

Vitamin D Deficiency

Abstract: Once foods in the United States were fortified with vitamin D, rickets appeared to have been conquered, and many considered major health problems from vitamin D deficiency resolved. But vitamin D deficiency is common. This review considers the role of vitamin D in skeletal and nonskeletal health and suggests strategies for the prevention and treatment of vitamin D deficiency.

Diagnosis and Management of the Metabolic Syndrome An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement

Abstract: The metabolic syndrome has received increased attention in the past few years. This statement from the American Heart Association (AHA) and the National Heart, Lung, and Blood Institute (NHLBI) is intended to provide up-to-date guidance for professionals on the diagnosis and management of the metabolic syndrome in adults. The metabolic syndrome is a constellation of interrelated risk factors of metabolic origin— metabolic risk factors —that appear to directly promote the development of atherosclerotic cardiovascular disease (ASCVD).1 Patients with the metabolic syndrome also are at increased risk for developing type 2 diabetes mellitus. Another set of conditions, the underlying risk factors , give rise to the metabolic risk factors. In the past few years, several expert groups have attempted to set forth simple diagnostic criteria to be used in clinical practice to identify patients who manifest the multiple components of the metabolic syndrome. These criteria have varied somewhat in specific elements, but in general they include a combination of both underlying and metabolic risk factors. The most widely recognized of the metabolic risk factors are atherogenic dyslipidemia, elevated blood pressure, and elevated plasma glucose. Individuals with these characteristics commonly manifest a prothrombotic state and a pro-inflammatory state as well. Atherogenic dyslipidemia consists of an aggregation of lipoprotein abnormalities including elevated serum triglyceride and apolipoprotein B (apoB), increased small LDL particles, and a reduced level of HDL cholesterol (HDL-C). The metabolic syndrome is often referred to as if it were a discrete entity with a single cause. Available data suggest that it truly is a syndrome, ie, a grouping of ASCVD risk factors, but one that probably has more than one cause. Regardless of cause, the syndrome identifies individuals at an elevated risk for ASCVD. The magnitude of the increased risk can vary according to which components of the syndrome are …