Dietary and genetic risk scores and incidence of type 2 diabetes

Associations of Combined Genetic and Lifestyle Risks with Incident Type 2 Diabetes in the UK Biobank

Background

Type 2 diabetes (T2D) results from a complex interplay between genetic predisposition and lifestyle factors. Both genetic susceptibility and unhealthy lifestyle are known to be associated with elevated T2D risk. However, their combined effects on T2D risk are not well studied. We aimed to determine whether unhealthy modifiable health behaviors were associated with similar increases in the risk of incident T2D among individuals with different levels of genetic risk.

Methods

We performed a genetic risk score (GRS) by lifestyle interaction analysis within 332,251 non-diabetic individuals at baseline from the UK Biobank. Multi-ancestry GRS were calculated by summing the effects of 783 T2D-associated variants and ranked into tertiles. We used baseline self-reported data on smoking, BMI, physical activity level, and diet quality to categorize participants as having a healthy, intermediate, or unhealthy lifestyle. Cox proportional hazards regression models were used to generate adjusted hazards ratios (HR) of T2D risk and associated 95% confidence intervals (CI).

Results

During follow-up (median 13.6 years), 13,128 (4.0%) participants developed T2D. GRS (P < 0.001) and lifestyle classification (P < 0.001) were independently associated with increased risk for T2D. Compared with healthy lifestyle, unhealthy lifestyle was associated with increased T2D risk in all genetic risk strata, with adjusted HR ranging from 7.11 (low genetic risk) to 16.33 (high genetic risk).

Conclusions

High genetic risk and unhealthy lifestyle were the most significant contributors to the development of T2D. Individuals at all levels of genetic risk can greatly mitigate their risk for T2D through lifestyle modifications.

Healthy dietary pattern is associated with lower glycemia independently of the genetic risk of type 2 diabetes: a cross-sectional study in Finnish men

PURPOSE

Hyperglycemia is affected by lifestyle and genetic factors. We investigated if dietary patterns associate with glycemia in individuals with high or low genetic risk for type 2 diabetes (T2D).

METHODS

Men (n = 1577, 51-81 years) without T2D from the Metabolic Syndrome in Men (METSIM) cohort filled a food-frequency questionnaire and participated in a 2-hour oral glucose tolerance test. Polygenetic risk score (PRS) including 76 genetic variants was used to stratify participants into low or high T2D risk groups. We established two data-driven dietary patterns, termed healthy and unhealthy, and investigated their association with plasma glucose concentrations and hyperglycemia risk.

RESULTS

Healthy dietary pattern was associated with lower fasting and 2-hour plasma glucose, glucose area under the curve, and better insulin sensitivity (Matsuda insulin sensitivity index) and insulin secretion (disposition index) in unadjusted and adjusted models, whereas the unhealthy pattern was not. No interaction was observed between the patterns and PRS on glycemic measures. Healthy dietary pattern was negatively associated with the risk for hyperglycemia in an adjusted model (OR 0.69, 95% CI 0.51-0.95, in the highest tertile), whereas unhealthy pattern was not (OR 1.08, 95% CI 0.79-1.47, in the highest tertile). No interaction was found between diet and PRS on the risk for hyperglycemia (p = 0.69 for healthy diet, p = 0.54 for unhealthy diet).

CONCLUSION

Our findings suggest that healthy diet is associated with lower glucose concentrations and lower risk for hyperglycemia in men with no interaction with the genetic risk.

Ancestry Specific Polygenic Risk Score, Dietary Patterns, Physical Activity, and Cardiovascular Disease

It is unknown whether the impact of high diet quality and physical activity depends on the level of polygenic risk score (PRS) in different ancestries. Our cross-sectional study utilized de-identified data from 1987-2010 for self-reported European Americans (n = 6575) and African Americans (n = 1606). The high-risk PRS increased ASCVD risk by 59% (Risk Ratio (RR) = 1.59; 95% Confidence Interval:1.16-2.17) in the highest tertile for African Americans and by 15% (RR = 1.15; 1.13-1.30) and 18% (RR = 1.18; 1.04-1.35) in the second and highest tertiles compared to the lowest tertile in European Americans. Within the highest PRS tertiles, high physical activity-diet combinations (Dietary Approaches to Stop High Blood Pressure (DASH), Mediterranean, or Southern) reduced ASCVD risks by 9% (RR = 0.91; 0.85-0.96) to 15% (RR = 0.85; 0.80-0.90) in European Americans; and by 13% (RR = 0.87; 0.78-0.97) and 18% (RR = 0.82; 0.72-0.95) for DASH and Mediterranean diets, respectively, in African Americans. Top molecular pathways included fructose metabolism and catabolism linked to obesity, insulin resistance, and type 2 diabetes. Additional molecular pathways for African Americans were Vitamin D linked to depression and aging acceleration and death signaling associated with cancer. Effects of high diet quality and high physical activity can counterbalance the influences of genetically high-risk PRSs on ASCVD risk, especially in African Americans.

Genotype-based precision nutrition strategies for the prediction and clinical management of type 2 diabetes mellitus

Globally, type 2 diabetes mellitus (T2DM) is one of the most common metabolic disorders. T2DM physiopathology is influenced by complex interrelationships between genetic, metabolic and lifestyle factors (including diet), which differ between populations and geographic regions. In fact, excessive consumptions of high fat/high sugar foods generally increase the risk of developing T2DM, whereas habitual intakes of plant-based healthy diets usually exert a protective effect. Moreover, genomic studies have allowed the characterization of sequence DNA variants across the human genome, some of which may affect gene expression and protein functions relevant for glucose homeostasis. This comprehensive literature review covers the impact of gene-diet interactions on T2DM susceptibility and disease progression, some of which have demonstrated a value as biomarkers of personal responses to certain nutritional interventions. Also, novel genotype-based dietary strategies have been developed for improving T2DM control in comparison to general lifestyle recommendations. Furthermore, progresses in other omics areas (epigenomics, metagenomics, proteomics, and metabolomics) are improving current understanding of genetic insights in T2DM clinical outcomes. Although more investigation is still needed, the analysis of the genetic make-up may help to decipher new paradigms in the pathophysiology of T2DM as well as offer further opportunities to personalize the screening, prevention, diagnosis, management, and prognosis of T2DM through precision nutrition.

Ancestry Specific Polygenic Risk Score, Dietary Patterns, Physical Activity, and Cardiovascular Disease

Background

It is unknown whether the impact of high diet-quality and physical activity (PA) depends on the level of polygenic risk score (PRS) in different ancestries.

Objective

Determine the associations and interactions between high-risk PRSs, dietary patterns, and high PA with atherosclerotic cardiovascular disease (ASCVD) in European Americans (EAs) and African Americans (AAs). Another aim determined the molecular pathways of PRS-mapped genes and their relationships with dietary intake.

Methods

Cross-sectional analyses utilized de-identified data from 1987-2010 from 7-National Heart, Lung, and Blood Institute Candidate Gene Association Resource studies from the Database of Genotypes and Phenotypes studies for EAs (n=6,575) and AAs (n=1,606).

Results

The high-risk PRS increased ASCVD risk by 59% (Risk Ratio=1.59;95% Confidence Interval:1.16-2.17) in the highest tertile for AAs and by 15% (RR=1.15;1.13-1.30) and 18% (RR=1.18;1.04-1.35) in the second and highest tertiles compared to the lowest tertile in EAs. Within the highest PRS tertiles, high PA-diet combinations (Dietary Approaches to Stop High Blood Pressure (DASH), or Mediterranean, or Southern) reduced ASCVD risks by 9% (RR=0.91;0.85-0.96) to 15% (RR=0.85;0.80-0.90) in EAs; and by 13% (RR=0.87;0.78-0.97) and 18% (RR=0.82;0.72-0.95) for the DASH and Mediterranean diets, respectively in AAs. Top molecular pathways included fructose metabolism and catabolism linked to obesity, insulin resistance, and type 2 diabetes in both ancestries. Additional molecular pathways for AAs were Vitamin D linked to depression and aging acceleration; and death signaling associated with cancer.

Conclusions

Effects of high diet-quality and high PA can counterbalance the influences of genetically high-risk PRSs on ASCVD risk, especially in AAs.

Adherence to the EAT-Lancet diet, genetic susceptibility, and risk of type 2 diabetes in Swedish adults

BACKGROUND AND AIMS

In 2019, the EAT-Lancet Commission proposed a mainly plant-based diet that nurtures human health and supports environmental sustainability. However, its association with type 2 diabetes (T2D) has not been widely studied, and it remains unclear whether genetic susceptibility for T2D can modify this association. The aim was therefore to investigate the association between the EAT-Lancet diet and risk of T2D and assess whether the association differs by the genetic predisposition to T2D.

METHODS

A total of 24,494 participants from the Malmö Diet and Cancer study were analyzed. Dietary intake was assessed using a modified diet history methodology, and an EAT-Lancet diet index (range from 0 to 42 points) was constructed based on the EAT-Lancet reference diet. National and local registers were used to identify T2D cases during follow-up. Cox proportional hazards regression model was applied to estimate the association between the EAT-Lancet diet index and risk of T2D. Genetic predisposition to T2D was captured based on 116 single nucleotide polymorphisms.

RESULTS

During a median of 24.3 years of follow-up, 4197 (17.1 %) T2D cases were documented. Compared with those with the lowest adherence to the EAT-Lancet diet (≤13 points), participants who had the highest adherence (≥23 points) showed an 18 % (95 % CI: 4 %-30 %) lower risk of T2D (P for trend <0.01). There was no significant multiplicative interaction between genetic predisposition to T2D and the EAT-Lancet diet index (P = 0.59). Also, no significant additive interaction between the genetic risk and the EAT-Lancet diet was seen (P = 0.44). The highest risk was observed among the 22.9 % of the individuals with high genetic risk and low EAT-Lancet diet score (HR = 1.79; 95 % CI: 1.63, 1.96).

CONCLUSIONS

Our findings indicate that high adherence to the EAT-Lancet diet was associated with decreased risk of incident T2D among people with different genetic risks.

Optimization of a GC-MS method for the profiling of microbiota-dependent metabolites in blood samples: An application to type 2 diabetes and prediabetes

Changes in serum or plasma metabolome may reflect gut microbiota dysbiosis, which is also known to occur in patients with prediabetes and type 2 diabetes (T2DM). Thus, developing a robust method for the analysis of microbiota-dependent metabolites (MDMs) is an important issue. Gas chromatography with mass spectrometry (GC–MS) is a powerful approach enabling detection of a wide range of MDMs in biofluid samples with good repeatability and reproducibility, but requires selection of a suitable solvents and conditions. For this reason, we conducted for the first time the study in which, we demonstrated an optimisation of samples preparation steps for the measurement of 75 MDMs in two matrices. Different solvents or mixtures of solvents for MDMs extraction, various concentrations and volumes of derivatizing reagents as well as temperature programs at methoxymation and silylation step, were tested. The stability, repeatability and reproducibility of the 75 MDMs measurement were assessed by determining the relative standard deviation (RSD). Finally, we used the developed method to analyse serum samples from 18 prediabetic (PreDiab group) and 24 T2DM patients (T2DM group) from our 1000PLUS cohort. The study groups were homogeneous and did not differ in age and body mass index. To select statistically significant metabolites, T2DM vs. PreDiab comparison was performed using multivariate statistics. Our experiment revealed changes in 18 MDMs belonging to different classes of compounds, and seven of them, based on the SVM classification model, were selected as a panel of potential biomarkers, able to distinguish between patients with T2DM and prediabetes.

Recent Progress in Fluorescent Probes for Diabetes Visualization and Drug Therapy

Diabetes has become one of the most prevalent endocrine and metabolic diseases that threaten human health, and it is accompanied by serious complications. Therefore, it is vital and pressing to develop novel strategies or tools for prewarning and therapy of diabetes and its complications. Fluorescent probes have been widely applied in the detection of diabetes due to the fact of their attractive advantages. In this report, we comprehensively summarize the recent progress and development of fluorescent probes in detecting the changes in the various biomolecules in diabetes and its complications. We also discuss the design of fluorescent probes for monitoring diabetes in detail. We expect this review will provide new ideas for the development of fluorescent probes suitable for the prewarning and therapy of diabetes in future clinical transformation and application.

Metabolites of Gut Microbiota and Possible Implication in Development of Diabetes Mellitus

Diabetes mellitus is characterized by having a disorder of glucose metabolism. The types of diabetes mellitus include type 1 diabetes mellitus, type 2 diabetes mellitus, gestational diabetes mellitus, and other specific types of diabetes mellitus. Many risk factors contribute to diabetes mellitus mainly including genetics, environment, obesity, and diet. In the recent years, gut microbiota has been shown to be linked to the development of diabetes. It has been reported that the gut microbiota composition of diabetic patients is different from that of healthy people. Although the mechanism behind the abnormality remains to be explored, most hypotheses focus on the inflammation response and leaky gut in relation to the changes in production of endotoxins and metabolites derived from the intestinal flora. Consequently, the above-mentioned abnormalities trigger a series of metabolic changes, gradually leading to development of hyperglycemia, insulin resistance, and diabetes. This review is (i) to summarize the differences in gut microbiota between diabetic patients and healthy people, (ii) to discuss the underlying mechanism(s) by which how lipopolysaccharide, diet, and metabolites of the gut microbiota affect diabetes, and (iii) to provide a new insight in the prevention and treatment of diabetes.

Lipidomic risk scores are independent of polygenic risk scores and can predict incidence of diabetes and cardiovascular disease in a large population cohort

Type 2 diabetes (T2D) and cardiovascular disease (CVD) represent significant disease burdens for most societies and susceptibility to these diseases is strongly influenced by diet and lifestyle. Physiological changes associated with T2D or CVD, such has high blood pressure and cholesterol and glucose levels in the blood, are often apparent prior to disease incidence. Here we integrated genetics, lipidomics, and standard clinical diagnostics to assess future T2D and CVD risk for 4,067 participants from a large prospective population-based cohort, the Malmö Diet and Cancer-Cardiovascular Cohort. By training Ridge regression-based machine learning models on the measurements obtained at baseline when the individuals were healthy, we computed several risk scores for T2D and CVD incidence during up to 23 years of follow-up. We used these scores to stratify the participants into risk groups and found that a lipidomics risk score based on the quantification of 184 plasma lipid concentrations resulted in a 168% and 84% increase of the incidence rate in the highest risk group and a 77% and 53% decrease of the incidence rate in lowest risk group for T2D and CVD, respectively, compared to the average case rates of 13.8% and 22.0%. Notably, lipidomic risk correlated only marginally with polygenic risk, indicating that the lipidome and genetic variants may constitute largely independent risk factors for T2D and CVD. Risk stratification was further improved by adding standard clinical variables to the model, resulting in a case rate of 51.0% and 53.3% in the highest risk group for T2D and CVD, respectively. The participants in the highest risk group showed significantly altered lipidome compositions affecting 167 and 157 lipid species for T2D and CVD, respectively. Our results demonstrated that a subset of individuals at high risk for developing T2D or CVD can be identified years before disease incidence. The lipidomic risk, which is derived from only one single mass spectrometric measurement that is cheap and fast, is informative and could extend traditional risk assessment based on clinical assays.

Tolerable upper intake level for dietary sugars

Following a request from five European Nordic countries, the EFSA Panel on Nutrition, Novel Foods and Food Allergens (NDA) was tasked to provide scientific advice on a tolerable upper intake level (UL) or a safe level of intake for dietary (total/added/free) sugars based on available data on chronic metabolic diseases, pregnancy-related endpoints and dental caries. Specific sugar types (fructose) and sources of sugars were also addressed. The intake of dietary sugars is a well-established hazard in relation to dental caries in humans. Based on a systematic review of the literature, prospective cohort studies do not support a positive relationship between the intake of dietary sugars, in isocaloric exchange with other macronutrients, and any of the chronic metabolic diseases or pregnancy-related endpoints assessed. Based on randomised control trials on surrogate disease endpoints, there is evidence for a positive and causal relationship between the intake of added/free sugars and risk of some chronic metabolic diseases: The level of certainty is moderate for obesity and dyslipidaemia (> 50-75% probability), low for non-alcoholic fatty liver disease and type 2 diabetes (> 15-50% probability) and very low for hypertension (0-15% probability). Health effects of added vs. free sugars could not be compared. A level of sugars intake at which the risk of dental caries/chronic metabolic diseases is not increased could not be identified over the range of observed intakes, and thus, a UL or a safe level of intake could not be set. Based on available data and related uncertainties, the intake of added and free sugars should be as low as possible in the context of a nutritionally adequate diet. Decreasing the intake of added and free sugars would decrease the intake of total sugars to a similar extent. This opinion can assist EU Member States in setting national goals/recommendations.

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

Chile is one of the largest consumers of sugar-sweetened beverages (SSB) world-wide. However, it is unknown whether the effects from this highly industrialized food will mimic those reported in industrialized countries or whether they will be modified by local lifestyle or population genetics. Our goal is to evaluate the interaction effect between SSB intake and T2D susceptibility on fasting glucose. We calculated a weighted genetic risk score (GRSw) based on 16 T2D risk SNPs in 2828 non-diabetic participants of the MAUCO cohort. SSB intake was categorized in four levels using a food frequency questionnaire. Log-fasting glucose was regressed on SSB and GRSw tertiles while accounting for socio-demography, lifestyle, obesity, and Amerindian ancestry. Fasting glucose increased systematically per unit of GRSw (β = 0.02 ± 0.006, p = 0.00002) and by SSB intake (β[cat4] = 0.04 ± 0.01, p = 0.0001), showing a significant interaction, where the strongest effect was observed in the highest GRSw-tertile and in the highest SSB consumption category (β = 0.05 ± 0.02, p = 0.02). SNP-wise, SSB interacted with additive effects of rs7903146 (TCF7L2) (β = 0.05 ± 0.01, p = 0.002) and with the G/G genotype of rs10830963 (MTNRB1B) (β = 0.19 ± 0.05, p = 0.001). Conclusions: The association between SSB intake and fasting glucose in the Chilean population without diabetes is modified by T2D genetic susceptibility.

Effect of Diet Quality and Genetic Predisposition on Hemoglobin A1c and Type 2 Diabetes Risk: Gene-Diet Interaction Analysis of 357,419 Individuals

OBJECTIVE

To assess the interactions between diet quality and genetic predisposition to incident type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

Between 2006 and 2010, 357,419 participants with genetic and complete dietary data from the UK Biobank were enrolled and prospectively followed up to 2017. The genetic risk score (GRS) was calculated on the basis of 424 variants associated with T2D risk, and a higher GRS indicates a higher genetic predisposition to T2D. The adherence to a healthy diet was assessed by a diet quality score comprising 10 important dietary components, with a higher score representing a higher overall diet quality.

RESULTS

There were 5,663 incident T2D cases documented during an average of 8.1 years of follow-up. A significant negative interaction was observed between the GRS and the diet quality score. After adjusting for major risk factors, per SD increment in the GRS and the diet quality score was associated with a 54% higher and a 9% lower risk of T2D, respectively. A simultaneous increment of 1 SD in both the diet quality score and GRS was additionally associated with a 3% lower T2D risk due to the antagonistic interaction. In categorical analyses, a sharp reduction of 23% in T2D risk associated with a 1-SD increment in the diet quality score was detected among participants in the extremely high GRS group (GRS >95%). We also observed a strong negative interaction between the GRS and the diet quality score on the blood HbA1c level at baseline (P < 0.001).

CONCLUSIONS

The adherence to a healthy diet was associated with more reductions in blood HbA1c levels and subsequent T2D risk among individuals with a higher genetic risk. Our findings support tailoring dietary recommendations to an individual's genetic makeup for T2D prevention.

A Preliminary Study Showing the Impact of Genetic and Dietary Factors on GC-MS-Based Plasma Metabolome of Patients with and without PROX1-Genetic Predisposition to T2DM up to 5 Years Prior to Prediabetes Appearance

Risk factors for type 2 diabetes mellitus (T2DM) consist of a combination of an unhealthy, imbalanced diet and genetic factors that may interact with each other. Single nucleotide polymorphism (SNP) in the prospero homeobox 1 (PROX1) gene is a strong genetic susceptibility factor for this metabolic disorder and impaired β-cell function. As the role of this gene in T2DM development remains unclear, novel approaches are needed to advance the understanding of the mechanisms of T2DM development. Therefore, in this study, for the first time, postprandial changes in plasma metabolites were analysed by GC–MS in nondiabetic men with different PROX1 genotypes up to 5 years prior to prediabetes appearance. Eighteen contestants (12 with high risk (HR) and 6 with low risk (LR) genotype) participated in high-carbohydrate (HC) and normo-carbohydrate (NC) meal-challenge tests. Our study concluded that both meal-challenge tests provoked changes in 15 plasma metabolites (amino acids, carbohydrates, fatty acids and others) in HR, but not LR genotype carriers. Postprandial changes in the levels of some of the detected metabolites may be a source of potential specific early disturbances possibly associated with the future development of T2DM. Thus, accurate determination of these metabolites can be important for the early diagnosis of this metabolic disease.

A Genetic Risk Score Improves the Prediction of Type 2 Diabetes Mellitus in Mexican Youths but Has Lower Predictive Utility Compared With Non-Genetic Factors

Background

Type 2 diabetes (T2D) is a multifactorial disease caused by a complex interplay between environmental risk factors and genetic predisposition. To date, a total of 10 single nucleotide polymorphism (SNPs) have been associated with pediatric-onset T2D in Mexicans, with a small individual effect size. A genetic risk score (GRS) that combines these SNPs could serve as a predictor of the risk for pediatric-onset T2D.

Objective

To assess the clinical utility of a GRS that combines 10 SNPs to improve risk prediction of pediatric-onset T2D in Mexicans.

Methods

This case-control study included 97 individuals with pediatric-onset T2D and 84 controls below 18 years old without T2D. Information regarding family history of T2D, demographics, perinatal risk factors, anthropometric measurements, biochemical variables, lifestyle, and fitness scores were then obtained. Moreover, 10 single nucleotide polymorphisms (SNPs) previously associated with pediatric-onset T2D in Mexicans were genotyped. The GRS was calculated by summing the 10 risk alleles. Pediatric-onset T2D risk variance was assessed using multivariable logistic regression models and the area under the receiver operating characteristic curve (AUC).

Results

The body mass index Z-score (Z-BMI) [odds ratio (OR) = 1.7; p = 0.009] and maternal history of T2D (OR = 7.1; p < 0.001) were found to be independently associated with pediatric-onset T2D. No association with other clinical risk factors was observed. The GRS also showed a significant association with pediatric-onset T2D (OR = 1.3 per risk allele; p = 0.006). The GRS, clinical risk factors, and GRS plus clinical risk factors had an AUC of 0.66 (95% CI 0.56-0.75), 0.72 (95% CI 0.62-0.81), and 0.78 (95% CI 0.70-0.87), respectively (p < 0.01).

Conclusion

The GRS based on 10 SNPs was associated with pediatric-onset T2D in Mexicans and improved its prediction with modest significance. However, clinical factors, such the Z-BMI and family history of T2D, continue to have the highest predictive utility in this population.

Meat consumption and risk of 25 common conditions: outcome-wide analyses in 475,000 men and women in the UK Biobank study

BACKGROUND

There is limited prospective evidence on the association between meat consumption and many common, non-cancerous health outcomes. We examined associations of meat intake with risk of 25 common conditions (other than cancer).

METHODS

We used data from 474,985 middle-aged adults recruited into the UK Biobank study between 2006 and 2010 and followed up until 2017 (mean follow-up 8.0 years) with available information on meat intake at baseline (collected via touchscreen questionnaire), and linked hospital admissions and mortality data. For a large sub-sample (~ 69,000), dietary intakes were re-measured three or more times using an online, 24-h recall questionnaire.

RESULTS

On average, participants who reported consuming meat regularly (three or more times per week) had more adverse health behaviours and characteristics than participants who consumed meat less regularly, and most of the positive associations observed for meat consumption and health risks were substantially attenuated after adjustment for body mass index (BMI). In multi-variable adjusted (including BMI) Cox regression models corrected for multiple testing, higher consumption of unprocessed red and processed meat combined was associated with higher risks of ischaemic heart disease (hazard ratio (HRs) per 70 g/day higher intake 1.15, 95% confidence intervals (CIs) 1.07-1.23), pneumonia (1.31, 1.18-1.44), diverticular disease (1.19, 1.11-1.28), colon polyps (1.10, 1.06-1.15), and diabetes (1.30, 1.20-1.42); results were similar for unprocessed red meat and processed meat intakes separately. Higher consumption of unprocessed red meat alone was associated with a lower risk of iron deficiency anaemia (IDA: HR per 50 g/day higher intake 0.80, 95% CIs 0.72-0.90). Higher poultry meat intake was associated with higher risks of gastro-oesophageal reflux disease (HR per 30 g/day higher intake 1.17, 95% CIs 1.09-1.26), gastritis and duodenitis (1.12, 1.05-1.18), diverticular disease (1.10, 1.04-1.17), gallbladder disease (1.11, 1.04-1.19), and diabetes (1.14, 1.07-1.21), and a lower IDA risk (0.83, 0.76-0.90).

CONCLUSIONS

Higher unprocessed red meat, processed meat, and poultry meat consumption was associated with higher risks of several common conditions; higher BMI accounted for a substantial proportion of these increased risks suggesting that residual confounding or mediation by adiposity might account for some of these remaining associations. Higher unprocessed red meat and poultry meat consumption was associated with lower IDA risk.

Associations of carbohydrates and carbohydrate-rich foods with incidence of type 2 diabetes

Dietary carbohydrates have long been expected to be associated with risk of type 2 diabetes; however, the associations for many carbohydrates and carbohydrate-rich foods remain inconclusive. This study analysed associations between intakes of six types of carbohydrates and thirteen carbohydrate-rich foods with incident type 2 diabetes in 26 622 participants (61 % women) in the Malmö Diet and Cancer Study in southern Sweden. Dietary intake was assessed at baseline (1991-1996) by using a modified diet history method. During mean follow-up of 18 years, 4046 cases were identified. Adjusting for potential confounders (including lifestyle, BMI and dietary factors), comparing highest v. lowest quintile of intake, monosaccharides (hazard ratio (HR) 0·88; 95 % CI 0·79, 0·98; Ptrend = 0·02) and fruits (HR 0·91; 95 % CI 0·82, 1·01; Ptrend = 0·03) were inversely associated with incident type 2 diabetes, while disaccharides (HR 1·17; 95 % CI 1·04, 1·30; Ptrend = 0·002) and sweets (HR 1·09; 95 % CI 1·00, 1·19; Ptrend = 0·02) were positively associated. After stratification by sex, marmalade/honey/jam (HR 0·82; 95 % CI 0·72, 0·94; Ptrend < 0·001) and vegetables (HR 0·85; 95 % CI 0·73, 0·98; Ptrend = 0·06) were inversely associated with incident type 2 diabetes in men and chocolate (HR 1·26; 95 % CI 1·09, 1·46; Ptrend < 0·001) was positively associated in women. In conclusion, we identified inverse associations for intake of monosaccharides and fruits with type 2 diabetes risk, and positive associations for disaccharides and sweets. Additional sex-specific associations were also identified. Future studies are needed to explore these associations further.

Identification of Inflammatory and Disease-Associated Plasma Proteins that Associate with Intake of Added Sugar and Sugar-Sweetened Beverages and Their Role in Type 2 Diabetes Risk

It has been suggested that high intake of added sugar and sugar-sweetened beverages (SSBs) increase the level of circulating inflammatory proteins and that chronic inflammation plays a role in type 2 diabetes (T2D) development. We aim to examine how added sugar and SSB intake associate with 136 measured plasma proteins and C-reactive protein (CRP) in the Malmö Diet and Cancer-Cardiovascular Cohort (n = 4382), and examine if the identified added sugar- and SSB-associated proteins associate with T2D incidence. A two-step iterative resampling approach was used to internally replicate proteins that associated with added sugar and SSB intake. Nine proteins were identified to associate with added sugar intake, of which only two associated with T2D incidence (p < 0.00045). Seven proteins were identified to associate with SSB intake, of which six associated strongly with T2D incidence (p < 6.9 × 10-8). No significant associations were observed between added sugar and SSB intake and CRP concentrations. In summary, our elucidation of the relationship between plasma proteome and added sugar and SSB intake, in relation to future T2D risk, demonstrated that SSB intake, rather than the total intake of added sugar, was related to a T2D-pathological proteomic signature. However, external replication is needed to verify the findings.

The Role of Nutrition in the Prevention and Intervention of Type 2 Diabetes

Type 2 diabetes (T2D) is a rapidly growing epidemic, which leads to increased mortality rates and health care costs. Nutrients (namely, carbohydrates, fat, protein, mineral substances, and vitamin), sensing, and management are central to metabolic homeostasis, therefore presenting a leading factor contributing to T2D. Understanding the comprehensive effects and the underlying mechanisms of nutrition in regulating glucose metabolism and the interactions of diet with genetics, epigenetics, and gut microbiota is helpful for developing new strategies to prevent and treat T2D. In this review, we discuss different mechanistic pathways contributing to T2D and then summarize the current researches concerning associations between different nutrients intake and glucose homeostasis. We also explore the possible relationship between nutrients and genetic background, epigenetics, and metagenomics in terms of the susceptibility and treatment of T2D. For the specificity of individual, precision nutrition depends on the person’s genotype, and microbiota is vital to the prevention and intervention of T2D.

Consumption of red meat, genetic susceptibility, and risk of LADA and type 2 diabetes

Purpose

Red meat consumption is positively associated with type 1 (T1D) and type 2 (T2D) diabetes. We investigated if red meat consumption increases the risk of latent autoimmune diabetes in adults (LADA) and T2D, and potential interaction with family history of diabetes (FHD), HLA and TCF7L2 genotypes.

Methods

Analyses were based on Swedish case–control data comprising incident cases of LADA (n = 465) and T2D (n = 1528) with matched, population-based controls (n = 1789; n = 1553 in genetic analyses). Multivariable-adjusted ORs in relation to self-reported processed and unprocessed red meat intake were estimated by conditional logistic regression models. Attributable proportion (AP) due to interaction was used to assess departure from additivity of effects.

Results

Consumption of processed red meat was associated with increased risk of LADA (per one servings/day OR 1.27, 95% CI 1.07–1.52), whereas no association was observed for unprocessed red meat. For T2D, there was no association with red meat intake once BMI was taken into account. The combination of high (> 0.3 servings/day vs. less) processed red meat intake and high-risk HLA-DQB1 and -DRB1 genotypes yielded OR 8.05 (95% CI 4.86–13.34) for LADA, with indications of significant interaction (AP 0.53, 95% CI 0.32–0.73). Results were similar for the combination of FHD-T1D and processed red meat. No interaction between processed red meat intake and FHD-T2D or risk variants of TCF7L2 was seen in relation to LADA or T2D.

Conclusion

Consumption of processed but not unprocessed red meat may increase the risk of LADA, especially in individuals with FHD-T1D or high-risk HLA genotypes.

Electronic supplementary material

The online version of this article (10.1007/s00394-020-02285-2) contains supplementary material, which is available to authorized users.

Sociodemographic and lifestyle-related risk factors for identifying vulnerable groups for type 2 diabetes: a narrative review with emphasis on data from Europe

BACKGROUND

Type 2 diabetes mellitus (T2DM) comprises the vast majority of all diabetes cases in adults, with alarmingly increasing prevalence over the past few decades worldwide. A particularly heavy healthcare burden of diabetes is noted in Europe, where 8.8% of the population aged 20-79 years is estimated to have diabetes according to the International Diabetes Federation. Multiple risk factors are implicated in the pathogenesis of T2DM with complex underlying interplay and intricate gene-environment interactions. Thus, intense research has been focused on studying the role of T2DM risk factors and on identifying vulnerable groups for T2DM in the general population which can then be targeted for prevention interventions.

METHODS

For this narrative review, we conducted a comprehensive search of the existing literature on T2DM risk factors, focusing on studies in adult cohorts from European countries which were published in English after January 2000.

RESULTS

Multiple lifestyle-related and sociodemographic factors were identified as related to high T2DM risk, including age, ethnicity, family history, low socioeconomic status, obesity, metabolic syndrome and each of its components, as well as certain unhealthy lifestyle behaviors. As Europe has an increasingly aging population, multiple migrant and ethnic minority groups and significant socioeconomic diversity both within and across different countries, this review focuses not only on modifiable T2DM risk factors, but also on the impact of pertinent demographic and socioeconomic factors.

CONCLUSION

In addition to other T2DM risk factors, low socioeconomic status can significantly increase the risk for prediabetes and T2DM, but is often overlooked. In multinational and multicultural regions such as Europe, a holistic approach, which will take into account both traditional and socioeconomic/socioecological factors, is becoming increasingly crucial in order to implement multidimensional public health programs and integrated community-based interventions for effective T2DM prevention.

Precision Medicine in Lifestyle Medicine: The Way of the Future?

Precision medicine has captured the imagination of the medical community with visions of therapies precisely targeted to the specific individual's genetic, biological, social, and environmental profile. However, in practice it has become synonymous with genomic medicine. As such its successes have been limited, with poor predictive or clinical value for the majority of people. It adds little to lifestyle medicine, other than in establishing why a healthy lifestyle is effective in combatting chronic disease. The challenge of lifestyle medicine remains getting people to actually adopt, sustain, and naturalize a healthy lifestyle, and this will require an approach that treats the patient as a person with individual needs and providing them with suitable types of support. The future of lifestyle medicine is holistic and person-centered rather than technological.

Different domains of self-reported physical activity and risk of type 2 diabetes in a population-based Swedish cohort: the Malmö diet and Cancer study

BACKGROUND

While a dose-response relationship between physical activity and risk of diabetes has been demonstrated, few studies have assessed the relative importance of different measures of physical activity on diabetes risk. The aim was to examine the association between different self-reported measures of physical activity and risk of type 2 diabetes in a prospective cohort study.

METHODS

Out of 26,615 adults (45-74 years, 60% women) in the population-based Swedish Malmö Diet and Cancer Study cohort, 3791 type 2 diabetes cases were identified from registers during 17 years of follow-up. Leisure-time (17 activities), occupational and domestic physical activity were assessed through a questionnaire, and these and total physical activity were investigated in relation to type 2 diabetes risk.

RESULTS

All physical activity measures showed weak to modest associations with type 2 diabetes risk. The strongest association was found in the lower end of leisure-time physical activity in dose-response analysis at levels approximately below 22 MET-hrs/week (300 min/week) representing around 40% of the population. Compared with the lowest quintile, the moderate leisure-time physical activity category had a 28% (95% CI: 0.71, 0.87) decreased risk of type 2 diabetes. Total physical activity showed a similar, but weaker, association with diabetes risk as to that of leisure-time physical activity. Domestic physical activity was positively and linearly related to diabetes risk, HR = 1.11 (95% CI: 0.99, 1.25) comparing highest to lowest quintile. There was no association between occupational physical activity and diabetes risk.

CONCLUSION

A curvilinear association was observed between leisure-time physical activity and risk of diabetes. Beyond a threshold level of approximately 22 MET-hrs/week or 300 min/week, no additional risk reduction was observed with increase in physical activity.

Plasma Lipidome and Prediction of Type 2 Diabetes in the Population-Based Malmö Diet and Cancer Cohort

OBJECTIVE

Type 2 diabetes mellitus (T2DM) is associated with dyslipidemia, but the detailed alterations in lipid species preceding the disease are largely unknown. We aimed to identify plasma lipids associated with development of T2DM and investigate their associations with lifestyle.

RESEARCH DESIGN AND METHODS

At baseline, 178 lipids were measured by mass spectrometry in 3,668 participants without diabetes from the Malmö Diet and Cancer Study. The population was randomly split into discovery (n = 1,868, including 257 incident cases) and replication (n = 1,800, including 249 incident cases) sets. We used orthogonal projections to latent structures discriminant analyses, extracted a predictive component for T2DM incidence (lipid-PC_DM), and assessed its association with T2DM incidence using Cox regression and lifestyle factors using general linear models.

RESULTS

A T2DM-predictive lipid-PC_DM derived from the discovery set was independently associated with T2DM incidence in the replication set, with hazard ratio (HR) among subjects in the fifth versus first quintile of lipid-PC_DM of 3.7 (95% CI 2.2-6.5). In comparison, the HR of T2DM among obese versus normal weight subjects was 1.8 (95% CI 1.2-2.6). Clinical lipids did not improve T2DM risk prediction, but adding the lipid-PC_DM to all conventional T2DM risk factors increased the area under the receiver operating characteristics curve by 3%. The lipid-PC_DM was also associated with a dietary risk score for T2DM incidence and lower level of physical activity.

CONCLUSIONS

A lifestyle-related lipidomic profile strongly predicts T2DM development beyond current risk factors. Further studies are warranted to test if lifestyle interventions modifying this lipidomic profile can prevent T2DM.

Prevention of Potential Adverse Metabolic Effects of a Supplementation with Omega-3 Fatty Acids Using a Genetic Score Approach

INTRODUCTION

The consumption of long-chain omega-3 polyunsaturated fatty acids (n-3 PUFA) has been reported to have beneficial health effects, notably, by reducing plasma triglyceride levels. Nonetheless, a concomitant decrease in insulin sensitivity has also been observed, but is highly variable among subjects. Herein, we aimed to determine the importance of the genetic background in the interindividual variability of the insulin sensitivity response following an n-3 PUFA supplementation.

METHODS

A total of 210 participants completed a 6-week n-3 PUFA supplementation with 5 g/day of fish oil (providing 1.9-2.2 g of eicosapentaenoic acid + 1.1 g of docosahexaenoic acid). Insulin resistance was estimated by the homeostatic model assessment (HOMA-IR), and participants were further classified as high-risk or low-risk depending on their HOMA-IR change following the n-3 PUFA supplementation, as compared to pre-supplementation values. Genome-wide genotyping data were obtained for 138 participants using HumanOmni-5-Quad BeadChips containing 4,301,331 single nucleotide polymorphisms. A genome-wide association analysis (GWAS) was carried out between high-risk and low-risk participants. The population study was split into training (60%) and testing (40%) datasets to assess the predictive accuracy of a genetic risk score (GRS) constructed by summing the number of risk alleles.

RESULTS

Following the n-3 PUFA supplementation, 32 participants had increased HOMA-IR as compared to initial values and were classified as high risk (23.2%), whereas remaining subjects were classified as low risk (n = 106, 76.8%). A total of 8 loci had frequency differences between high-risk and low-risk participants at a suggestive GWAS association threshold (p value <1 × 10-5). After applying 10-fold cross validation, the GRS showed a significant association with the risk of increased HOMA-IR in the testing dataset (OR = 3.16 [95% CI, 1.85-7.14]), with a predictive accuracy of 0.85, and explained 40% of variation in HOMA-IR change.

CONCLUSIONS

These results suggest that the genetic background has a relevant role in the interindividual variability observed in the insulin sensitivity response following an n-3 PUFA supplementation. Subjects being at risk of insulin sensitivity lowering following an n-3 PUFA supplementation may be identified using genetic-based precision nutrition approaches.

Validity of polygenic risk scores: are we measuring what we think we are?

Polygenic risk scores (PRSs) have become the standard for quantifying genetic liability in the prediction of disease risks. PRSs are generally constructed as weighted sum scores of risk alleles using effect sizes from genome-wide association studies as their weights. The construction of PRSs is being improved with more appropriate selection of independent single-nucleotide polymorphisms (SNPs) and optimized estimation of their weights but is rarely reflected upon from a theoretical perspective, focusing on the validity of the risk score. Borrowing from psychometrics, this paper discusses the validity of PRSs and introduces the three main types of validity that are considered in the evaluation of tests and measurements: construct, content, and criterion validity. This introduction is followed by a discussion of three topics that challenge the validity of PRS, namely, their claimed independence of clinical risk factors, the consequences of relaxing SNP inclusion thresholds and the selection of SNP weights. This discussion of the validity of PRS reminds us that we need to keep questioning if weighted sums of risk alleles are measuring what we think they are in the various scenarios in which PRSs are used and that we need to keep exploring alternative modeling strategies that might better reflect the underlying biological pathways.

Gene-lifestyle interaction on risk of type 2 diabetes: A systematic review

The pathophysiological influence of gene-lifestyle interactions on the risk to develop type 2 diabetes (T2D) is currently under intensive research. This systematic review summarizes the evidence for gene-lifestyle interactions regarding T2D incidence. MEDLINE, EMBASE, and Web of Science were systematically searched until 31 January 2019 to identify publication with (a) prospective study design; (b) T2D incidence; (c) gene-diet, gene-physical activity, and gene-weight loss intervention interaction; and (d) population who are healthy or prediabetic. Of 66 eligible publications, 28 reported significant interactions. A variety of different genetic variants and dietary factors were studied. Variants at TCF7L2 were most frequently investigated and showed interactions with fiber and whole grain on T2D incidence. Further gene-diet interactions were reported for, eg, a western dietary pattern with a T2D-GRS, fat and carbohydrate with IRS1 rs2943641, and heme iron with variants of HFE. Physical activity showed interaction with HNF1B, IRS1, PPARγ, ADRA2B, SLC2A2, and ABCC8 variants and weight loss interventions with ENPP1, PPARγ, ADIPOR2, ADRA2B, TNFα, and LIPC variants. However, most findings represent single study findings obtained in European ethnicities. Although some interactions have been reported, their conclusiveness is still low, as most findings were not yet replicated across multiple study populations.

Genotypes of HLA, TCF7L2, and FTO as potential modifiers of the association between sweetened beverage consumption and risk of LADA and type 2 diabetes

Purpose

Sweetened beverage consumption is associated with type 2 diabetes (T2D) and LADA. We investigated to what extent this association is mediated by BMI and whether it is modified by genotypes of HLA, TCF7L2 rs7903146, or FTO rs9939609.

Methods

Swedish case–control data including incident cases of LADA (n = 386) and T2D (n = 1253) with matched population-based controls (n = 1545) was used. We estimated adjusted ORs of diabetes (95% CI) in relation to sweetened beverage intake (per daily 200 mL serving) and genotypes. The impact of BMI was estimated using causal mediation methodology. Associations with HOMA-IR and HOMA-B were explored through linear regression.

Results

Sweetened beverage intake was associated with increased risk of LADA (OR 1.15, 95% CI 1.03–1.29) and T2D (OR 1.21, 1.11–1.32). BMI was estimated to mediate 17% (LADA) and 56% (T2D) of the total risk. LADA was associated with risk variants of HLA (3.44, 2.63–4.50) and TCF7L2 (1.27, 1.00–1.61) but not FTO. Only among non-carriers of high-risk HLA genotypes was sweetened beverage intake associated with risk of LADA (OR 1.32, 1.06–1.56) and HOMA-IR (beta = 0.162, p = 0.0047). T2D was associated with TCF7L2 and FTO but not HLA, and the risk conferred by sweetened beverages appeared modified by FTO (OR 1.45, 95% CI 1.21–1.73 in non-carriers).

Conclusions

Our findings suggest that sweetened beverages are associated with LADA and T2D partly through mediation by excess weight, but possibly also through other mechanisms including adverse effects on insulin sensitivity. These effects seem more pronounced in individuals without genetic susceptibility.

Electronic supplementary material

The online version of this article (10.1007/s00394-019-01893-x) contains supplementary material, which is available to authorized users.

Lack of Association of Coffee Consumption with the Prevalence of Self-Reported Type 2 Diabetes Mellitus in a Mexican Population: A Cross-Sectional Study

It is estimated that almost 366 million people are currently suffering from diabetes mellitus worldwide. However, it has been suggested that coffee consumption has a protective effect against the development of type 2 diabetes mellitus. This association has been observed in many regions around the world. Today, there are no reports in Mexico regarding this association. Therefore, the aim of this study was to assess the association between coffee intake and self-reported type 2 diabetes mellitus in the southeastern part of Mexico. This study included 1277 residents of Comalcalco, a municipality of Tabasco State, Mexico. We calculated the prevalence for diabetes and performed multivariate analysis using multiple logistic regressions to evaluate the combined association with type 2 diabetes mellitus. The prevalence of the diabetes was 12.52% (95% CI: 10.67⁻14.38). The majority of people surveyed (77.29%; 95% CI: 74.95⁻79.60) indicated they were coffee drinkers. The results of multivariate analysis showed a non-significant relationship between the number of cups of coffee drank and type 2 diabetes mellitus. The adjusted odds ratio gave the following values: 1.20, (95% CI: 0.59⁻2.41) for non-daily consumption; 1.66 (0.82⁻3.34), for 1 cup of coffee peer day, and 1.49 (0.78⁻2.86) for 2⁻3 cups. Subsequently, an adjustment was made for age, gender, marital status, education, alcohol consumption, and cigarette smoking. In our population, we did not observe an association between coffee intake and its protective relationship with self-reported type 2 diabetes mellitus.