The Association between Fasting Glucose and Sugar Sweetened Beverages Intake Is Greater in Latin Americans with a High Polygenic Risk Score for Type 2 Diabetes Mellitus

López-Portillo, María Lourdes; Huidobro, Andrea; Tobar-Calfucoy, Eduardo; Yáñez, Cristian; Retamales-Ortega, Rocío; Garrido‐Tapia, Macarena; Acevedo, Johanna; Paredes, Fabio; Cid-Ossandon, Vicente; Ferreccio, Catterina; Verdugo, Ricardo A.

doi:10.3390/nu14010069

Cited by 10 publications

(14 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, SSB consumption was positively associated with fasting glucose levels ( P < 0.0001). This association was intensified in participants consuming two or more SSBs per day (β = 0.04 ± 0.01, P < 0.0001) and having the highest genetic susceptibility (β = 0.02 ± 0.006, P < 0.00002), independent of the BMI [4 ▪ ]. A meta-analysis of 11 cohort studies with 34 748 participants of European descent and without diabetes revealed similar findings [5].…”

Section: Carbohydrates and Development Of Obesitymentioning

confidence: 71%

“…Consumption of SSBs is associated with increased obesity and the risk for cardiovascular diseases (CVDs) [3 ▪▪ ]. Recently, López-Portillo et al [4 ▪ ] published data from the prospective cohort study MAUCO concerning SSB consumption, fasting glucose and a polygenetic risk score in 2 828 Latin Americans without diabetes. To assess the genetic impact of an association between SSB consumption and fasting glucose levels, a weighed polygenetic risk score based on 16 gene variants was built.…”

Section: Carbohydrates and Development Of Obesitymentioning

confidence: 99%

See 1 more Smart Citation

Carbohydrate intake – current knowledge on weight management

Bayer¹,

Holzapfel²

2022

Current Opinion in Clinical Nutrition &Amp; Metabolic Care

View full text Add to dashboard Cite

Purpose of review Carbohydrates are the main contributor to daily energy intake and, thus, might play an essential role in the development and treatment of obesity. This nonsystematic literature overview summarized current knowledge about the association between carbohydrate intake (quantity and quality) and weight management. Recent findings There is scientific evidence for the association between the quality of carbohydrates and body weight or metabolic parameters (e.g. fasting glucose). Thus, dietary intake of high-quality carbohydrates should be preferred over food with a low carbohydrate quality. In contrast, heterogeneous data are available for the association between the amount of carbohydrate intake and anthropometric parameters (e.g. body weight, body fat). Regulation of dietary intake and body weight is complex. For instance, gene-diet interactions might play a role in carbohydrate intake and metabolism. Summary There is evidence for the association between intake of high-quality carbohydrates and body weight. However, for the treatment of obesity, a negative energy balance is crucial. The success in weight loss was independent of the quantity and quality of carbohydrate intake. To sum up, recently published literature does not change the current opinion about carbohydrate intake and obesity.

show abstract

Section: Carbohydrates and Development Of Obesitymentioning

confidence: 71%

Section: Carbohydrates and Development Of Obesitymentioning

confidence: 99%

Carbohydrate intake – current knowledge on weight management

Bayer¹,

Holzapfel²

2022

Current Opinion in Clinical Nutrition &Amp; Metabolic Care

View full text Add to dashboard Cite

show abstract

“…Though they found the differential effect of the combined lifestyle status on T2D among the PRS groups, no statistically significant interaction between the PRS and the combined lifestyle was found by the Cox regression model using the T2D onset‐age. López‐Portillo et al (2021) reported the interaction between T2D PRS and SSB intake on fasting glucose. They constructed T2D RPS using 16 T2D GWAS SNPs and tested PRS as a continuous variable and as a categorical variable by classifying individuals into tertiles of PRS.…”

Section: Discussionmentioning

confidence: 99%

“…The EPIC InterAct Case‐Cohort Study performed the interaction analysis of T2D incidence between PRS (using 49 T2D GWAS SNPs) and various lifestyle factors including age, sex, family history of T2D, body mass index (BMI), waist circumference, physical activity, and dietary factors (Langenberg et al, 2014). Moreover, the interaction analysis between T2D PRS (using 16 T2D GWAS SNPs) and sugar‐sweetened beverages (SSB) consumption on fasting glucose in Chileans were reported (Lopez‐Portillo et al, 2021) and identified a significant interaction ( β ± SE = 0.02 ± 0.006, p = 0.004). There have been several interaction studies in the European population, however, there are few reported studies of gene‐environment interactions, so far, in Asian populations (J. Kim et al, 2016, 2017; Lee et al, 2015; Villegas et al, 2011, 2012, 2014).…”

Section: Introductionmentioning

confidence: 99%

Gene‐environment interaction in type 2 diabetes in Korean cohorts: Interaction of a type 2 diabetes polygenic risk score with triglyceride and cholesterol on fasting glucose levels

Lim

Kang

et al. 2022

Genetic Epidemiology

View full text Add to dashboard Cite

Type 2 diabetes (T2D) is caused by genetic and environmental factors as well as gene‐environment interactions. However, these interactions have not been systematically investigated. We analyzed these interactions for T2D and fasting glucose levels in three Korean cohorts, HEXA, KARE, and CAVAS, using the baseline data with a multiple regression model. Two polygenic risk scores for T2D (PRST2D) and fasting glucose (PRSFG) were calculated using 488 and 82 single nucleotide polymorphisms (SNP) for T2D and fasting glucose, respectively, which were extracted from large‐scaled genome‐wide association studies with multiethnic data. Both lifestyle risk factors and T2D‐related biochemical measurements were assessed. The effect of interactions between PRST2D‐triglyceride (TG) and PRST2D‐total cholesterol (TC) on fasting glucose levels was observed as follows: β ± SE = 0.0005 ± 0.0001, p = 1.06 × 10−19 in HEXA, β ± SE = 0.0008 ± 0.0001, p = 2.08 × 10−8 in KARE for TG; β ± SE = 0.0006 ± 0.0001, p = 2.00 × 10−6 in HEXA, β ± SE = 0.0020 ± 0.0004, p = 2.11 × 10−6 in KARE, β ± SE = 0.0007 ± 0.0004, p = 0.045 in CAVAS for TC. PRST2D‐based classification of the participants into four groups showed that the fasting glucose levels in groups with higher PRST2D were more adversely affected by both the TG and TC. In conclusion, blood TG and TC levels may affect the fasting glucose level through interaction with T2D genetic factors, suggesting the importance of consideration of gene‐environment interaction in the preventive medicine of T2D.

show abstract

“… A heat map showing the findings for gene-lifestyle interactions on diabetes traits. López-Portillo et al ( 161 ), GRS-16 Type 2 Diabetes (T2D) risk SNPs = MTNR1B (rs10830963); TCF7L2 (rs7903146); CDKAL1 (rs7756992); ADCY5 (rs11717195); ANK1 (rs516946); BCAR1 (rs7202877); CDC123 (rs11257655); DUSP9 (rs5945326); GRB14 (rs3923113); RASGRP1 (rs7403531); TLE4 (rs17791513); TLE1 (rs2796441); ZBED3 (rs6878122) . …”

Section: Methodsmentioning

confidence: 99%

Interactions between genetic and lifestyle factors on cardiometabolic disease-related outcomes in Latin American and Caribbean populations: A systematic review

et al. 2023

View full text Add to dashboard Cite

IntroductionThe prevalence of cardiometabolic diseases has increased in Latin American and the Caribbean populations (LACP). To identify gene-lifestyle interactions that modify the risk of cardiometabolic diseases in LACP, a systematic search using 11 search engines was conducted up to May 2022.MethodsEligible studies were observational and interventional studies in either English, Spanish, or Portuguese. A total of 26,171 publications were screened for title and abstract; of these, 101 potential studies were evaluated for eligibility, and 74 articles were included in this study following full-text screening and risk of bias assessment. The Appraisal tool for Cross-Sectional Studies (AXIS) and the Risk Of Bias In Non-Randomized Studies—of Interventions (ROBINS-I) assessment tool were used to assess the methodological quality and risk of bias of the included studies.ResultsWe identified 122 significant interactions between genetic and lifestyle factors on cardiometabolic traits and the vast majority of studies come from Brazil (29), Mexico (15) and Costa Rica (12) with FTO, APOE, and TCF7L2 being the most studied genes. The results of the gene-lifestyle interactions suggest effects which are population-, gender-, and ethnic-specific. Most of the gene-lifestyle interactions were conducted once, necessitating replication to reinforce these results.DiscussionThe findings of this review indicate that 27 out of 33 LACP have not conducted gene-lifestyle interaction studies and only five studies have been undertaken in low-socioeconomic settings. Most of the studies were cross-sectional, indicating a need for longitudinal/prospective studies. Future gene-lifestyle interaction studies will need to replicate primary research of already studied genetic variants to enable comparison, and to explore the interactions between genetic and other lifestyle factors such as those conditioned by socioeconomic factors and the built environment. The protocol has been registered on PROSPERO, number CRD42022308488.Systematic review registrationhttps://clinicaltrials.gov, identifier CRD420223 08488.

show abstract

The Association between Fasting Glucose and Sugar Sweetened Beverages Intake Is Greater in Latin Americans with a High Polygenic Risk Score for Type 2 Diabetes Mellitus

Cited by 10 publications

References 53 publications

Carbohydrate intake – current knowledge on weight management

Carbohydrate intake – current knowledge on weight management

Gene‐environment interaction in type 2 diabetes in Korean cohorts: Interaction of a type 2 diabetes polygenic risk score with triglyceride and cholesterol on fasting glucose levels

Interactions between genetic and lifestyle factors on cardiometabolic disease-related outcomes in Latin American and Caribbean populations: A systematic review

Contact Info

Product

Resources

About