Publications

OBJECTIVE To examine the secular trends in risk factors, estimate their impact on type 2 diabetes burden from 1991 to 2011, and project trends in the next 20 years. RESEARCH DESIGN AND METHODS Risk factor distributions were based on data from the China Health and Nutrition Survey 1991–2011. Diabetes cases attributable to all nonoptimal levels of each risk factor were estimated by applying the comparative risk assessment method. RESULTS In 2011, high BMI was the leading individual attributable factor for diabetes cases in China responsible for 43.8 million diabetes cases with a population-attributable fraction of 46.8%. Low whole-grain intake and high refined grain intake were the leading dietary risk factors in China responsible for 37.8 million and 21.8 million diabetes-attributable cases, respectively. The number of attributable diabetes cases associated with low physical activity, high blood pressure, and current smoking was 29.5, 21.6, and 9.8 million, respectively. Although intakes of low-fat dairy products, nuts, fruit, vegetables, and fish and seafood increased moderately over time, the average intake was below optimal levels in 2011 and were responsible for 15.8, 11.3, 9.9, 6.0, 3.6, and 2.6 million diabetes cases, respectively. Meanwhile, intakes of processed meat, red meat, and sugar-sweetened beverage showed increasing trends over time and were responsible for 2.8, 1.8, and 0.5 million diabetes cases, respectively, in 2011. CONCLUSIONS A high BMI and low intake of whole grains but high intake of refined grains are the most important individual risk factors related to Chinese diabetes burden; low physical activity and high blood pressure also significantly contributed.

Salivary amylase, encoded by the AMY1 gene, is responsible for the digestion of carbohydrates. We investigated associations of AMY1 genetic variations with general and central adiposity changes considering dietary carbohydrate intake among 32,054 adults from four prospective cohort studies. A genetic risk score (GRS) was calculated based on nine AMY1 single-nucleotide polymorphisms, with higher AMY1-GRS indicating higher activity of salivary amylase. We meta-analyzed interactions between AMY1-GRS and dietary intake for changes in general and central adiposity over 5.5–10 years. We found that carbohydrate food intake significantly altered associations of AMY1-GRS with changes in BMI (Pinteraction = 0.001) and waist circumference (Pinteraction < 0.001). Results were consistent and significant in female cohorts rather than in male cohorts. Among women, higher AMY1-GRS was associated with more increases in adiposity if dietary carbohydrate food intake was high, while higher AMY1-GRS was associated with less gains in adiposity when the dietary intake was low. Also, in a 2-year randomized dietary intervention trial, associations of AMY1-GRS with changes in weight (Pinteraction = 0.023) and waist circumference (Pinteraction = 0.037) were significantly modified by carbohydrate intake. Our results suggest the importance of precision nutrition strategies considering participants’ genetic adaptation to carbohydrate-rich diets in regulating general and central adiposity.

OBJECTIVE High molecular weight (HMW) adiponectin is a predominant isoform of circulating adiponectin and has been related to type 2 diabetes. Previous linkage studies suggest that different genetic components might be involved in determining HMW and total adiponectin levels. RESEARCH DESIGN AND METHODS We performed a genome-wide association study (GWAS) of serum HMW adiponectin levels in individuals of European ancestry drawn from the Nurses’ Health Study (NHS) (N = 1,591). The single nucleotide polymorphisms (SNPs) identified in the GWAS analysis were replicated in an independent cohort of Europeans (N = 626). We examined the associations of the identified variations with diabetes risk and metabolic syndrome. RESULTS We identified a novel locus near the FER gene (5q21) at a genome-wide significance level, best represented by SNP rs10447248 (P = 4.69 × 10−8). We also confirmed that variations near the adiponectin-encoding ADIPOQ locus (3q27) were related to serum HMW adiponectin levels. In addition, we found that FER SNP rs10447248 was related to HDL cholesterol levels (P = 0.009); ADIPOQ variation was associated with fasting glucose (P = 0.04), HDL cholesterol (P = 0.04), and a metabolic syndrome score (P = 0.002). CONCLUSIONS Our results suggest that different loci may be involved in regulation of circulating HMW adiponectin levels and provide novel insight into the mechanisms that affect HMW adiponectin homeostasis.

A typical genome-wide association study searches for associations between single nucleotide polymorphisms (SNPs) and a univariate phenotype. However, there is a growing interest to investigate associations between genomics data and multivariate phenotypes, for example, in gene expression or metabolomics studies. A common approach is to perform a univariate test between each genotype-phenotype pair, and then to apply a stringent significance cutoff to account for the large number of tests performed. However, this approach has limited ability to uncover dependencies involving multiple variables. Another trend in the current genetics is the investigation of the impact of rare variants on the phenotype, where the standard methods often fail owing to lack of power when the minor allele is present in only a limited number of individuals.We propose a new statistical approach based on Bayesian reduced rank regression to assess the impact of multiple SNPs on a high-dimensional phenotype. Because of the method's ability to combine information over multiple SNPs and phenotypes, it is particularly suitable for detecting associations involving rare variants. We demonstrate the potential of our method and compare it with alternatives using the Northern Finland Birth Cohort with 4702 individuals, for whom genome-wide SNP data along with lipoprotein profiles comprising 74 traits are available. We discovered two genes (XRCC4 and MTHFD2L) without previously reported associations, which replicated in a combined analysis of two additional cohorts: 2390 individuals from the Cardiovascular Risk in Young Finns study and 3659 individuals from the FINRISK study.R-code freely available for download at http://users.ics.aalto.fi/pemartti/gene_metabolome/.

the relative risk for type 2 diabetes in men in the top quintile of dairy intake was 0.77 (95% confidence interval [CI], 0.62-0.95; P for trend, .003) compared with those in the lowest quintile. Each serving-per-day increase in total dairy intake was associated with a 9% lower risk for type 2 diabetes (multivariate relative risk, 0.91; 95% CI, 0.85-0.97). The corresponding relative risk was 0.88 (95% CI, 0.81-0.94) for low-fat dairy intake and 0.99 (95% CI, 0.91-1.07) for high-fat dairy intake. The association did not vary significantly according to body mass index (25 vs 25 kg/m 2 ; P for interaction, .57). Conclusion: Dietary patterns characterized by higher dairy intake, especially low-fat dairy intake, may lower the risk of type 2 diabetes in men. Arch Intern Med. 2005;165:997-1003