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Qi, Lu

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Qi, Lu

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Now showing 1 - 10 of 19
  • Publication

    Identification of New Genetic Risk Variants for Type 2 Diabetes

    (Public Library of Science, 2010) Shu, Xiao Ou; Long, Jirong; Cai, Qiuyin; Xiang, Yong-Bing; Tai, E. Shyong; Li, Xiangyang; Lin, Xu; Chow, Wong-Ho; Go, Min Jin; Seielstad, Mark; Li, Huaixing; Yu, Kai; Wen, Wanqing; Shi, Jiajun; Han, Bok-Ghee; Sim, Xue Ling; Liu, Liegang; Kim, Hyung-Lae; Ng, Daniel P. K.; Lee, Jong-Young; Gao, Yu-Tang; Visscher, Peter M.; Qi, Lu; Cho, Yoon; Bao, Wei; Cornelis, Marilyn; Qi, Qibin; Kim, Young Jin; Li, Chun; Zheng, Wei; Hu, Frank

    Although more than 20 genetic susceptibility loci have been reported for type 2 diabetes (T2D), most reported variants have small to moderate effects and account for only a small proportion of the heritability of T2D, suggesting that the majority of inter-person genetic variation in this disease remains to be determined. We conducted a multistage, genome-wide association study (GWAS) within the Asian Consortium of Diabetes to search for T2D susceptibility markers. From 590,887 SNPs genotyped in 1,019 T2D cases and 1,710 controls selected from Chinese women in Shanghai, we selected the top 2,100 SNPs that were not in linkage disequilibrium (r(^2) less than 0.2) with known T2D loci for in silico replication in three T2D GWAS conducted among European Americans, Koreans, and Singapore Chinese. The 5 most promising SNPs were genotyped in an independent set of 1,645 cases and 1,649 controls from Shanghai, and 4 of them were further genotyped in 1,487 cases and 3,316 controls from 2 additional Chinese studies. Consistent associations across all studies were found for rs1359790 (13q31.1), rs10906115 (10p13), and rs1436955 (15q22.2) with P-values (per allele OR, 95%CI) of 6.49×10(^{−9}) (1.15, 1.10–1.20), 1.45×10(^{−8}) (1.13, 1.08–1.18), and 7.14×10(^{−7}) (1.13, 1.08–1.19), respectively, in combined analyses of 9,794 cases and 14,615 controls. Our study provides strong evidence for a novel T2D susceptibility locus at 13q31.1 and the presence of new independent risk variants near regions (10p13 and 15q22.2) reported by previous GWAS.

  • Publication

    Genetic Predisposition to Dyslipidemia and Type 2 Diabetes Risk in Two Prospective Cohorts

    (American Diabetes Association, 2012) Qi, Qibin; Liang, Liming; Doria, Alessandro; Hu, Frank; Qi, Lu

    Dyslipidemia has been associated with type 2 diabetes, but it remains unclear whether dyslipidemia plays a causal role in type 2 diabetes. We aimed to examine the association between the genetic predisposition to dyslipdemia and type 2 diabetes risk. The current study included 2,447 patients with type 2 diabetes and 3,052 control participants of European ancestry from the Nurses’ Health Study and the Health Professionals Follow-up Study. Genetic predisposition to dyslipidemia was estimated by three genotype scores of lipids (LDL cholesterol, HDL cholesterol, and triglycerides) on the basis of the established loci for blood lipids. Linear relation analysis indicated that the HDL cholesterol and triglyceride genotype scores, but not the LDL cholesterol genotype score, were linearly related to elevated type 2 diabetes risk. Each point of the HDL cholesterol and triglyceride genotype scores was associated with a 3% (odds ratio [OR] 1.03 [95% CI 1.01–1.04]) and a 2% (1.02 [1.00–1.04]) increased risk of developing type 2 diabetes, respectively. The ORs were 1.39 (1.17–1.65) and 1.19 (1.01–1.41) for type 2 diabetes by comparing extreme quartiles of the HDL cholesterol genotype score and triglyceride genotype score, respectively. In conclusion, genetic predisposition to low HDL cholesterol or high triglycerides is related to elevated type 2 diabetes risk.

  • Publication

    Dietary Intake, FTO Genetic Variants, and Adiposity: A Combined Analysis of Over 16,000 Children and Adolescents

    (American Diabetes Association, 2015) Qi, Qibin; Downer, Mary; Kilpeläinen, Tuomas O.; Taal, H. Rob; Barton, Sheila J.; Ntalla, Ioanna; Standl, Marie; Boraska, Vesna; Huikari, Ville; Kiefte-de Jong, Jessica C.; Körner, Antje; Lakka, Timo A.; Liu, Gaifen; Magnusson, Jessica; Okuda, Masayuki; Raitakari, Olli; Richmond, Rebecca; Scott, Robert A.; Bailey, Mark E.S.; Scheuermann, Kathrin; Holloway, John W.; Inskip, Hazel; Isasi, Carmen R.; Mossavar-Rahmani, Yasmin; Jaddoe, Vincent W.V.; Laitinen, Jaana; Lindi, Virpi; Melén, Erik; Pitsiladis, Yannis; Pitkänen, Niina; Snieder, Harold; Heinrich, Joachim; Timpson, Nicholas J.; Wang, Tao; Yuji, Hinoda; Zeggini, Eleftheria; Dedoussis, George V.; Kaplan, Robert C.; Wylie-Rosett, Judith; Loos, Ruth J.F.; Hu, Frank; Qi, Lu

    The FTO gene harbors variation with the strongest effect on adiposity and obesity risk. Previous data support a role for FTO variation in influencing food intake. We conducted a combined analysis of 16,094 boys and girls aged 1–18 years from 14 studies to examine the following: 1) the association between the FTO rs9939609 variant (or a proxy) and total energy and macronutrient intake; and 2) the interaction between the FTO variant and dietary intake, and the effect on BMI. We found that the BMI-increasing allele (minor allele) of the FTO variant was associated with increased total energy intake (effect per allele = 14.3 kcal/day [95% CI 5.9, 22.7 kcal/day], P = 6.5 × 10−4), but not with protein, carbohydrate, or fat intake. We also found that protein intake modified the association between the FTO variant and BMI (interactive effect per allele = 0.08 SD [0.03, 0.12 SD], P for interaction = 7.2 × 10−4): the association between FTO genotype and BMI was much stronger in individuals with high protein intake (effect per allele = 0.10 SD [0.07, 0.13 SD], P = 8.2 × 10−10) than in those with low intake (effect per allele = 0.04 SD [0.01, 0.07 SD], P = 0.02). Our results suggest that the FTO variant that confers a predisposition to higher BMI is associated with higher total energy intake, and that lower dietary protein intake attenuates the association between FTO genotype and adiposity in children and adolescents.

  • Publication

    Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry

    (Oxford University Press, 2015) Nettleton, Jennifer A.; Follis, Jack L.; Ngwa, Julius S.; Smith, Caren E.; Ahmad, Shafqat; Tanaka, Toshiko; Wojczynski, Mary K.; Voortman, Trudy; Lemaitre, Rozenn N.; Kristiansson, Kati; Nuotio, Marja-Liisa; Houston, Denise K.; Perälä, Mia-Maria; Qi, Qibin; Sonestedt, Emily; Manichaikul, Ani; Kanoni, Stavroula; Ganna, Andrea; Mikkilä, Vera; North, Kari E.; Siscovick, David S.; Harald, Kennet; Mckeown, Nicola M.; Johansson, Ingegerd; Rissanen, Harri; Liu, Yongmei; Lahti, Jari; Hu, Frank; Bandinelli, Stefania; Rukh, Gull; Rich, Stephen; Booij, Lisanne; Dmitriou, Maria; Ax, Erika; Raitakari, Olli; Mukamal, Kenneth; Männistö, Satu; Hallmans, Göran; Jula, Antti; Ericson, Ulrika; Jacobs,, David R.; Van Rooij, Frank J. A.; Deloukas, Panos; Sjögren, Per; Kähönen, Mika; Djousse, Luc; Perola, Markus; Barroso, Inês; Hofman, Albert; Stirrups, Kathleen; Viikari, Jorma; Uitterlinden, André G.; Kalafati, Ioanna P.; Franco, Oscar H.; Mozaffarian, Dariush; Salomaa, Veikko; Borecki, Ingrid B.; Knekt, Paul; Kritchevsky, Stephen B.; Eriksson, Johan G.; Dedoussis, George V.; Qi, Lu; Ferrucci, Luigi; Orho-Melander, Marju; Zillikens, M. Carola; Ingelsson, Erik; Lehtimäki, Terho; Renström, Frida; Cupples, L. Adrienne; Loos, Ruth J. F.; Franks, Paul

    Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist–hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006–0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

  • Publication

    FTO Genotype and 2-Year Change in Body Composition and Fat Distribution in Response to Weight-Loss Diets: The POUNDS LOST Trial

    (American Diabetes Association, 2012) Zhang, Xiaomin; Qi, Qibin; Zhang, Cuilin; Hu, Frank; Sacks, Frank; Qi, Lu

    Recent evidence suggests that the fat mass and obesity-associated gene (FTO) genotype may interact with dietary intakes in relation to adiposity. We tested the effect of FTO variant on weight loss in response to 2-year diet interventions. FTO rs1558902 was genotyped in 742 obese adults who were randomly assigned to one of four diets differing in the proportions of fat, protein, and carbohydrate. Body composition and fat distribution were measured by dual-energy x-ray absorptiometry and computed tomography. We found significant modification effects for intervention varying in dietary protein on 2-year changes in fat-free mass, whole body total percentage of fat mass, total adipose tissue mass, visceral adipose tissue mass, and superficial adipose tissue mass (for all interactions, P < 0.05). Carriers of the risk allele had a greater reduction in weight, body composition, and fat distribution in response to a high-protein diet, whereas an opposite genetic effect was observed on changes in fat distribution in response to a low-protein diet. Likewise, significant interaction patterns also were observed at 6 months. Our data suggest that a high-protein diet may be beneficial for weight loss and improvement of body composition and fat distribution in individuals with the risk allele of the FTO variant rs1558902.

  • Publication

    Genetic Predisposition to High Blood Pressure Associates With Cardiovascular Complications Among Patients With Type 2 Diabetes: Two Independent Studies

    (American Diabetes Association, 2012) Qi, Qibin; Forman, John; Jensen, Majken; Flint, Alan; Curhan, Gary; Rimm, Eric; Hu, Frank; Qi, Lu

    Hypertension and type 2 diabetes (T2D) commonly coexist, and both conditions are major risk factors for cardiovascular disease (CVD). We aimed to examine the association between genetic predisposition to high blood pressure and risk of CVD in individuals with T2D. The current study included 1,005 men and 1,299 women with T2D from the Health Professionals Follow-up Study and Nurses’ Health Study, of whom 732 developed CVD. A genetic predisposition score was calculated on the basis of 29 established blood pressure–associated variants. The genetic predisposition score showed consistent associations with risk of CVD in men and women. In the combined results, each additional blood pressure–increasing allele was associated with a 6% increased risk of CVD (odds ratio [OR] 1.06 [95% CI 1.03–1.10]). The OR was 1.62 (1.22–2.14) for risk of CVD comparing the extreme quartiles of the genetic predisposition score. The genetic association for CVD risk was significantly stronger in patients with T2D than that estimated in the general populations by a meta-analysis (OR per SD of genetic score 1.22 [95% CI 1.10–1.35] vs. 1.10 [1.08–1.12]; I2 = 71%). Our data indicate that genetic predisposition to high blood pressure is associated with an increased risk of CVD in individuals with T2D.

  • Publication

    IRS1 Genotype Modulates Metabolic Syndrome Reversion in Response to 2-Year Weight-Loss Diet Intervention: The POUNDS LOST trial

    (American Diabetes Association, 2013) Qi, Qibin; Xu, Min; Wu, Hongyu; Liang, Liming; Champagne, Catherine M.; Bray, George A.; Sacks, Frank; Qi, Lu

    OBJECTIVE Genetic variants near IRS1 are associated with features of the metabolic syndrome (MetS). We examined whether genetic variants near IRS1 might modulate the effects of diets varying in fat content on the MetS status in a 2-year weight-loss trial. RESEARCH DESIGN AND METHODS Two variants near IRS1, rs1522813 and rs2943641, were genotyped in 738 overweight/obese adults (age 60 ± 9 years; BMI 32.7 ± 3.9 kg/m2) randomly assigned to one of four weight-loss diets (a deficit of 750 kcal/day of caloric intake from baseline) varying in macronutrient contents for 2 years. We compared MetS status of high-fat (40% of caloric intake; n = 370) and low-fat (20% caloric intake; n = 368) diet groups differentiated by genotypes (rs1522813 A-allele carriers and noncarriers and rs2943641T-allele carriers and noncarriers). RESULTS Among rs1522813 A-allele carriers, the reversion rates of the MetS were higher in the high-fat diet group than those in the low-fat diet group over the 2-year intervention (P = 0.002), while no significant difference between diet groups was observed among noncarriers (P = 0.27). The genetic modulation on dietary effect was independent of weight changes. The odds ratio (OR) for the 2-year reversion of the MetS was 2.88 (95% CI 1.25–6.67) comparing the high-fat and low-fat diets among rs1522813 A-allele carriers, while the corresponding OR was 0.83 (0.36–1.92) in noncarriers. The variant rs2943641 was not observed to modulate dietary effects on the MetS status. CONCLUSIONS Our data suggest that high-fat weight-loss diets might be more effective in the management of the MetS compared with low-fat diets among individuals with the A-allele of the rs1522813 variant near IRS1.

  • Publication

    Multiple Nonglycemic Genomic Loci Are Newly Associated With Blood Level of Glycated Hemoglobin in East Asians

    (American Diabetes Association, 2014) Chen, Peng; Takeuchi, Fumihiko; Lee, Jong-Young; Li, Huaixing; Wu, Jer-Yuarn; Liang, Jun; Long, Jirong; Tabara, Yasuharu; Goodarzi, Mark O.; Pereira, Mark A.; Kim, Young Jin; Go, Min Jin; Stram, Daniel O.; Vithana, Eranga; Khor, Chiea-Chuen; Liu, Jianjun; Liao, Jiemin; Ye, Xingwang; Wang, Yiqin; Lu, Ling; Young, Terri L.; Lee, Jeannette; Thai, Ah Chuan; Cheng, Ching-Yu; van Dam, Rob M.; Friedlander, Yechiel; Heng, Chew-Kiat; Koh, Woon-Puay; Chen, Chien-Hsiun; Chang, Li-Ching; Pan, Wen-Harn; Qi, Qibin; Isono, Masato; Zheng, Wei; Cai, Qiuyin; Gao, Yutang; Yamamoto, Ken; Ohnaka, Keizo; Takayanagi, Ryoichi; Kita, Yoshikuni; Ueshima, Hirotsugu; Hsiung, Chao A.; Cui, Jinrui; Sheu, Wayne H.-H.; Rotter, Jerome I.; Chen, Yii-Der I.; Hsu, Chris; Okada, Yukinori; Kubo, Michiaki; Takahashi, Atsushi; Tanaka, Toshihiro; van Rooij, Frank J.A.; Ganesh, Santhi K.; Huang, Jinyan; Huang, Tao; Yuan, Jianmin; Hwang, Joo-Yeon; Gross, Myron D.; Assimes, Themistocles L.; Miki, Tetsuro; Shu, Xiao-Ou; Qi, Lu; Chen, Yuan-Tson; Lin, Xu; Aung, Tin; Wong, Tien-Yin; Teo, Yik-Ying; Kim, Bong-Jo; Kato, Norihiro; Tai, E-Shyong

    Glycated hemoglobin A1c (HbA1c) is used as a measure of glycemic control and also as a diagnostic criterion for diabetes. To discover novel loci harboring common variants associated with HbA1c in East Asians, we conducted a meta-analysis of 13 genome-wide association studies (GWAS; N = 21,026). We replicated our findings in three additional studies comprising 11,576 individuals of East Asian ancestry. Ten variants showed associations that reached genome-wide significance in the discovery data set, of which nine (four novel variants at TMEM79 [P value = 1.3 × 10−23], HBS1L/MYB [8.5 × 10−15], MYO9B [9.0 × 10−12], and CYBA [1.1 × 10−8] as well as five variants at loci that had been previously identified [CDKAL1, G6PC2/ABCB11, GCK, ANK1, and FN3KI]) showed consistent evidence of association in replication data sets. These variants explained 1.76% of the variance in HbA1c. Several of these variants (TMEM79, HBS1L/MYB, CYBA, MYO9B, ANK1, and FN3K) showed no association with either blood glucose or type 2 diabetes. Among individuals with nondiabetic levels of fasting glucose (<7.0 mmol/L) but elevated HbA1c (≥6.5%), 36.1% had HbA1c <6.5% after adjustment for these six variants. Our East Asian GWAS meta-analysis has identified novel variants associated with HbA1c as well as demonstrated that the effects of known variants are largely transferable across ethnic groups. Variants affecting erythrocyte parameters rather than glucose metabolism may be relevant to the use of HbA1c for diagnosing diabetes in these populations.

  • Publication

    Birth Weight, Genetic Susceptibility, and Adulthood Risk of Type 2 Diabetes

    (American Diabetes Association, 2012) Li, Yanping; Qi, Qibin; Workalemahu, Tsegaselassie; Hu, Frank; Qi, Lu

    OBJECTIVE Both stressful intrauterine milieus and genetic susceptibility have been linked to later-life diabetes risk. The current study aims to examine the interaction between low birth weight, a surrogate measure of stressful intrauterine milieus, and genetic susceptibility in relation to risk of type 2 diabetes in adulthood. RESEARCH DESIGN AND METHODS The analysis included two independent, nested case-control studies of 2,591 type 2 diabetic case subjects and 3,052 healthy control subjects. We developed two genotype scores: an obesity genotype score based on 32 BMI-predisposing variants and a diabetes genotype score based on 35 diabetes-predisposing variants. RESULTS Obesity genotype scores showed a stronger association with type 2 diabetes risk in individuals with low birth weight. In low–birth weight individuals, the multivariable-adjusted odds ratio (OR) was 2.55 (95% CI 1.34–4.84) by comparing extreme quartiles of the obesity genotype score, while the OR was 1.27 (1.04–1.55) among individuals with birth weight >2.5 kg (P for interaction = 0.017). We did not observe significant interaction between diabetes genotype scores and birth weight with regard to risk of type 2 diabetes. In a comparison of extreme quartiles of the diabetes gene score, the multivariable-adjusted OR was 3.80 (1.76–8.24) among individuals with low birth weight and 2.27 (1.82–2.83) among those with high birth weight (P for interaction = 0.16). CONCLUSIONS Our data suggest that low birth weight and genetic susceptibility to obesity may synergistically affect adulthood risk of type 2 diabetes.

  • Publication

    Gene × Physical Activity Interactions in Obesity: Combined Analysis of 111,421 Individuals of European Ancestry

    (Public Library of Science, 2013) Ahmad, Shafqat; Rukh, Gull; Varga, Tibor V.; Ali, Ashfaq; Kurbasic, Azra; Shungin, Dmitry; Ericson, Ulrika; Koivula, Robert W.; Chu, Audrey Yu-lei; Rose, Lynda M.; Ganna, Andrea; Qi, Qibin; Stančáková, Alena; Sandholt, Camilla H.; Elks, Cathy E.; Curhan, Gary; Jensen, Majken; Tamimi, Rulla; Allin, Kristine H.; Jørgensen, Torben; Brage, Soren; Langenberg, Claudia; Aadahl, Mette; Grarup, Niels; Linneberg, Allan; Paré, Guillaume; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Boehnke, Michael; Hamsten, Anders; Mohlke, Karen L.; Pasquale, Louis; Pedersen, Oluf; Scott, Robert A.; Ridker, Paul; Ingelsson, Erik; Laakso, Markku; Hansen, Torben; Qi, Lu; Wareham, Nicholas J.; Chasman, Daniel; Hallmans, Göran; Hu, Frank; Renström, Frida; Orho-Melander, Marju; Franks, Paul W.

    Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age2, sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, Pinteraction = 0.014 vs. n = 71,611, Pinteraction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (Pinteraction = 0.003) and the SEC16B rs10913469 (Pinteraction = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal.