Trimethylamine N-oxide (TMAO) is a circulating microbiome-derived metabolite implicated in the development of atherosclerosis and cardiovascular disease (CVD). We investigated whether plasma levels... Show moreTrimethylamine N-oxide (TMAO) is a circulating microbiome-derived metabolite implicated in the development of atherosclerosis and cardiovascular disease (CVD). We investigated whether plasma levels of TMAO, its precursors (betaine, carnitine, deoxycarnitine, choline), and TMAO-to-precursor ratios are associated with clinical outcomes, including CVD and mortality. This was followed by an in-depth analysis of their genetic, gut microbial, and dietary determinants. The analyses were conducted in five Dutch prospective cohort studies including 7834 individuals. To further investigate association results, Mendelian Randomization (MR) was also explored. We found only plasma choline levels (hazard ratio [HR] 1.17, [95% CI 1.07; 1.28]) and not TMAO to be associated with CVD risk. Our association analyses uncovered 10 genome-wide significant loci, including novel genomic regions for betaine (6p21.1, 6q25.3), choline (2q34, 5q31.1), and deoxycarnitine (10q21.2, 11p14.2) comprising several metabolic gene associations, for example, CPS1 or PEMT. Furthermore, our analyses uncovered 68 gut microbiota associations, mainly related to TMAO-to-precursors ratios and the Ruminococcaceae family, and 16 associations of food groups and metabolites including fish-TMAO, meat-carnitine, and plant-based food-betaine associations. No significant association was identified by the MR approach. Our analyses provide novel insights into the TMAO pathway, its determinants, and pathophysiological impact on the general population. Show less
Background & aimsInflammation is involved in the pathogenesis of cataract, age-related macular degeneration (AMD), and possibly open-angle glaucoma (OAG). We assessed whether the inflammatory... Show moreBackground & aimsInflammation is involved in the pathogenesis of cataract, age-related macular degeneration (AMD), and possibly open-angle glaucoma (OAG). We assessed whether the inflammatory potential of diet (quantified using the dietary inflammatory index; DII) affects the incidence of these common blinding age-related eye diseases. Serum inflammation markers were investigated as possible mediators.MethodsParticipants aged >45 years were selected from the prospective, population-based Rotterdam Study. From 1991 onwards, every 4–5 years, participants underwent extensive eye examinations. At baseline, blood samples and dietary data (using food frequency questionnaires) were collected. The DII was adapted based on the data available. Of the 7436 participants free of eye diseases at baseline, 4036 developed incident eye diseases during follow-up (cataract = 2895, early-intermediate AMD = 891, late AMD = 81, OAG = 169).ResultsThe adapted DII (aDII) ranged from −4.26 (i.e., anti-inflammatory) to 4.53 (i.e., pro-inflammatory). A higher aDII was significantly associated with increased inflammation. A higher neutrophil-lymphocyte ratio (NLR) was associated with an increased risk of cataract and AMD. Additionally, complement component 3c (C3c) and systemic immune-inflammation index (SII) were associated with increased risks of cataract and late AMD, respectively. Every point increase in the aDII was associated with a 9% increased risk of cataract (Odds ratio [95% confidence interval]: 1.09 [1.04–1.14]). The NLR and C3c partly mediated this association. We also identified associations of the aDII with risk of AMD (early-intermediate AMD, OR [95% CI]: 1.11 [1.03–1.19]; late AMD, OR [95% CI]: 1.24 [1.02–1.53]). The NLR partly mediated these associations. The aDII was not associated with OAG.ConclusionsA pro-inflammatory diet was associated with increased risks of cataract and AMD. Particularly the NLR, a marker of subclinical inflammation, appears to be implicated. These findings are relevant for patients with AMD and substantiate the current recommendations to strive for a healthy lifestyle to prevent blindness. Show less
Kuiper, L.M.; Polinder-Bos, H.A.; Bizzarri, D.; Vojinovic, D.; Vallerga, C.L.; Beekman, M.; ... ; Meurs, J.B.J. van 2023
Biological age captures a person’s age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers... Show moreBiological age captures a person’s age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment. Show less
BackgroundSuboptimal vitamin D status is common in people with celiac disease (CeD), a disease that can be characterized by the presence of serum anti-tissue transglutaminase antibodies (TG2A) (i.e... Show moreBackgroundSuboptimal vitamin D status is common in people with celiac disease (CeD), a disease that can be characterized by the presence of serum anti-tissue transglutaminase antibodies (TG2A) (i.e., TG2A positivity). To date, it remains unclear whether childhood TG2A positivity is associated with vitamin D status and how this potential association can be explained by other factors than malabsorption only, since vitamin D is mainly derived from exposure to sunlight. The aim of our study was therefore to assess whether childhood TG2A positivity is associated with vitamin D concentrations, and if so, to what extent this association can be explained by sociodemographic and lifestyle factors.MethodsThis cross-sectional study was embedded in the Generation R Study, a population-based prospective cohort. We measured serum anti-tissue transglutaminase antibodies (TG2A) concentrations and serum 25-hydroxyvitamin D (25(OH)D) concentrations of 3994 children (median age of 5.9 years). Children with serum TG2A concentrations >= 7 U/mL were considered TG2A positive. To examine associations between TG2A positivity and 25(OH)D concentrations, we performed multivariable linear regression, adjusted for sociodemographic and lifestyle factors.ResultsVitamin D deficiency (serum 25(OH)D < 50 nmol/L) was found in 17 out of 54 TG2A positive children (31.5%), as compared to 1182 out of 3940 TG2A negative children (30.0%). Furthermore, TG2A positivity was not associated with 25(OH)D concentrations (beta -2.20; 95% CI -9.72;5.33 for TG2A positive vs. TG2A negative children), and this did not change after adjustment for confounders (beta -1.73, 95% CI -8.31;4.85).ConclusionsOur findings suggest there is no association between TG2A positivity and suboptimal vitamin D status in the general pediatric population. However, the overall prevalence of vitamin D deficiency in both populations was high, suggesting that screening for vitamin D deficiency among children, regardless of TG2A positivity, would be beneficial to ensure early dietary intervention if needed. Show less
Maas, S.C.E.; Vidaki, A.; Teumer, A.; Costeira, R.; Wilson, R.; Dongen, J. van; ... ; Kayser, M. 2021
Background Information on long-term alcohol consumption is relevant for medical and public health research, disease therapy, and other areas. Recently, DNA methylation-based inference of alcohol... Show moreBackground Information on long-term alcohol consumption is relevant for medical and public health research, disease therapy, and other areas. Recently, DNA methylation-based inference of alcohol consumption from blood was reported with high accuracy, but these results were based on employing the same dataset for model training and testing, which can lead to accuracy overestimation. Moreover, only subsets of alcohol consumption categories were used, which makes it impossible to extrapolate such models to the general population. By using data from eight population-based European cohorts (N = 4677), we internally and externally validated the previously reported biomarkers and models for epigenetic inference of alcohol consumption from blood and developed new models comprising all data from all categories. Results By employing data from six European cohorts (N = 2883), we empirically tested the reproducibility of the previously suggested biomarkers and prediction models via ten-fold internal cross-validation. In contrast to previous findings, all seven models based on 144-CpGs yielded lower mean AUCs compared to the models with less CpGs. For instance, the 144-CpG heavy versus non-drinkers model gave an AUC of 0.78 +/- 0.06, while the 5 and 23 CpG models achieved 0.83 +/- 0.05, respectively. The transportability of the models was empirically tested via external validation in three independent European cohorts (N = 1794), revealing high AUC variance between datasets within models. For instance, the 144-CpG heavy versus non-drinkers model yielded AUCs ranging from 0.60 to 0.84 between datasets. The newly developed models that considered data from all categories showed low AUCs but gave low AUC variation in the external validation. For instance, the 144-CpG heavy and at-risk versus light and non-drinkers model achieved AUCs of 0.67 +/- 0.02 in the internal cross-validation and 0.61-0.66 in the external validation datasets. Conclusions The outcomes of our internal and external validation demonstrate that the previously reported prediction models suffer from both overfitting and accuracy overestimation. Our results show that the previously proposed biomarkers are not yet sufficient for accurate and robust inference of alcohol consumption from blood. Overall, our findings imply that DNA methylation prediction biomarkers and models need to be improved considerably before epigenetic inference of alcohol consumption from blood can be considered for practical applications. Show less
Context: Adult obesity is associated with chronic low-grade inflammation and may give rise to future chronic disease. However, it is unclear whether adiposity-related inflammation is already... Show moreContext: Adult obesity is associated with chronic low-grade inflammation and may give rise to future chronic disease. However, it is unclear whether adiposity-related inflammation is already apparent in childhood.Objective: To study associations between child adiposity measures with circulating monocytes and naive and memory subsets in CD4, CD8, and gamma delta T cell lineages.Methods: Ten-year-old children (n = 890) from the Generation R Cohort underwent dual-energy x-ray absorptiometry and magnetic resonance imaging for body composition (body mass index [BMI], fat mass index [FMI], android-to-gynoid fat mass ratio, visceral fat index, liver fat fraction). Blood samples were taken for detailed immunophenotyping of leukocytes by 11-color flow cytometry.Results: Several statistically significant associations were observed. A 1-SD increase in total FMI was associated with +8.4% (95% CI 2.0, 15.2) V delta 2(+)V gamma 9(+) and +7.4% (95% CI 2.4, 12.5) CD8(TEMRO)(+) cell numbers. A 1-SD increase in visceral fat index was associated with +10.7% (95% CI 3.3, 18.7) V delta 2(+)V gamma 9(+) and +8.3% (95% CI 2.6, 14.4) CD8(TEMRO)(+) cell numbers. Higher android-to-gynoid fat mass ratio was only associated with higher V delta 2(+)V gamma 9(+) T cells. Liver fat was associated with higher CD8(TEMRO)(+) cells but not with V delta 2(+)V gamma 9(+) T cells. Only liver fat was associated with lower Th17 cell numbers: a 1-SD increase was associated with -8.9% (95% CI -13.7, -3.7) Th17 cells. No associations for total CD8(+), CD4(+) T cells, or monocytes were observed. BMI was not associated with immune cells.Conclusion: Higher V delta 2(+)V gamma 9(+) and CD8(TEMRO)(+) cell numbers in children with higher visceral fat index could reflect presence of adiposity-related inflammation in children with adiposity of a general population. Show less
BACKGROUND: ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in... Show moreBACKGROUND: ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the CHREBP locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the CHREBP locus and dyslipidemia.METHODS: Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63599) and the UK Biobank (N=59220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near CHREBP were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake.RESULTS: In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (beta, 2.12 [95% CI, 1.16-3.07] mg/dL per allele; P<0.0001), but not significantly among the lowest SSB consumers (P=0.81; P-Diff<0.0001). Similar results were observed for 2 additional variants (rs35709627 and rs71556736). For triglyceride, rs55673514 was positively associated with triglyceride concentrations only among the highest SSB consumers (beta, 0.06 [95% CI, 0.02-0.09] In-mg/dL per allele, P=0.001) but not the lowest SSB consumers (P=0.84; P-Diff=0.0005).CONCLUSIONS: Our results identified genetic variants in the CHREBP locus that may protect against SSB-associated reductions in HDL-C and other variants that may exacerbate SSB-associated increases in triglyceride concentrations. Show less
Purpose To investigate the longitudinal association between the macronutrient composition of the diet and frailty. Methods Data were obtained from 5205 Dutch middle-aged and older adults... Show morePurpose To investigate the longitudinal association between the macronutrient composition of the diet and frailty. Methods Data were obtained from 5205 Dutch middle-aged and older adults participating in the Rotterdam Study. Frailty was measured using a frailty index based on the accumulation of 38 health-related deficits, score between 0 and 100, and a higher score indicating more frailty. Frailty was assessed at baseline and 11 years later (range of 23 years). Macronutrient intake was assessed using food-frequency questionnaires. The association between macronutrients and frailty over time was evaluated using multivariable linear regression, adjusted for the frailty index at baseline, energy intake, and other relevant confounders. All analyses were performed in strata of BMI. Results Median frailty index score was 13.8 points (IQR 9.6; 19.1) at baseline and increased by a median of 2.3 points (IQR - 2.0; 7.6) after 11 years. Overall, we found no significant associations between intake of carbohydrates or fat and frailty over time. We did observe a significant positive association between an iso-energetic intake of 10 g protein and frailty over time (beta 0.31 (95% CI 0.06; 0.55)) which was mainly driven by animal protein (beta 0.31 (95% CI 0.07; 0.56)). It did not depend on whether it was substituted fat or carbohydrates. Conclusions Our findings suggest that a reduction in the intake of animal protein may improve the overall health status over time in a relatively healthy population. More research is needed on the optimal macronutrient composition of the diet and frailty in more vulnerable populations. Show less
Meddens, S.F.W.; Vlaming, R. de; Bowers, P.; Burik, C.A.P.; Linner, R.K.; Lee, C.; ... ; Lifelines Cohort Study 2020
We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We... Show moreWe conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 x 10(-8)), while five of the 21 lead SNPs reach suggestive significance (P < 1 x 10(-5)) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (r(g) approximate to 0.15-0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|r(g)| approximate to 0.1-0.3) and positive genetic correlations with physical activity (r(g) approximate to 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (r(g) approximate to-0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction. Show less
Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We... Show moreSmoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p< 1x10(-7) (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D. Show less
Epidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study,... Show moreEpidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (beta = - 0.76, 95% CI - 2.45 to 1.08 mmHg), 0.06 mmHg lower diastolic blood pressure (beta = - 0.06, 95% CI - 0.93 to 0.87 mmHg), or pulse pressure (beta = - 0.65, 95% CI - 1.38 to 0.69 mmHg, all p > 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses. Show less
Objective: We aimed to validate a food-frequency questionnaire (FFQ) for Dutch pregnant women, against three 24 h-recalls and blood concentrations of B-vitamins and fatty acids, using the method of... Show moreObjective: We aimed to validate a food-frequency questionnaire (FFQ) for Dutch pregnant women, against three 24 h-recalls and blood concentrations of B-vitamins and fatty acids, using the method of triads. Methods: We included 83 pregnant women from the general population of Rotterdam, the Netherlands, at a median gestational age of 15.6 weeks. Participants completed three non-consecutive 24 h-recalls, and subsequently filled out the 293-item FFQ. Participants provided blood samples from which we analyzed serum folate and vitamin B12, as well as red blood cell folate, linoleic acid, and total saturated, monounsaturated, and polyunsaturated fatty acids. Results: Estimated energy intake did not differ between the FFQ and 24 h-recalls. Deattenuated Pearson's correlation coefficients, between energy-adjusted nutrient intake estimates from the FFQ and the 24 h-recalls, ranged from 0.41 (fat) to 0.88 (fiber) for macronutrients, and were around 0.6 for most micronutrients, except for vitamin E (0.27). Using the triad method, we obtained validity coefficients of 0.86 (95% Confidence Interval (CI) 0.36, 1.00) for serum folate, 0.86 (95% CI 0.18, 1.00) for red blood cell folate, and 1.00 (95% CI 0.42, 1.00) for vitamin B12. Validity coefficients for serum fatty acids ranged from 0.22 to 0.67. Conclusion: This FFQ is a reliable tool for estimating intake of energy, macronutrients, folate and vitamin B12 among women in mid-pregnancy. Show less
Toorn, J.E. van der; Cepeda, M.; Kiefte-de Jong, J.C.; Franco, O.H.; Voortman, T.; Schoufour, J.D. 2020
Purpose Several studies have reported seasonal variation in intake of food groups and certain nutrients. However, whether this could lead to a seasonal pattern of diet quality has not been... Show morePurpose Several studies have reported seasonal variation in intake of food groups and certain nutrients. However, whether this could lead to a seasonal pattern of diet quality has not been addressed. We aimed to describe the seasonality of diet quality, and to examine the contribution of the food groups included in the dietary guidelines to this seasonality. Methods Among 9701 middle-aged and elderly participants of the Rotterdam Study, a prospective population-based cohort, diet was assessed using food-frequency questionnaires (FFQ). Diet quality was measured as adherence to the Dutch dietary guidelines, and expressed in a diet quality score ranging from 0 to 14 points. The seasonality of diet quality and of the food group intake was examined using cosinor linear mixed models. Models were adjusted for sex, age, cohort, energy intake, physical activity, body mass index, comorbidities, and education. Results Diet quality had a seasonal pattern with a winter-peak (seasonal variation = 0.10 points, December-peak) especially among participants who were men, obese and of high socio-economic level. This pattern was mostly explained by the seasonal variation in the intake of legumes (seasonal variation = 3.52 g/day, December-peak), nuts (seasonal variation = 0.78 g/day, January-peak), sugar-containing beverages (seasonal variation = 12.96 milliliters/day, June-peak), and dairy (seasonal variation = 17.52 g/day, June-peak). Conclusions Diet quality varies seasonally with heterogeneous seasonality of food groups counteractively contributing to the seasonal pattern in diet quality. This seasonality should be considered in future research on dietary behavior. Also, season-specific recommendations and policies are required to improve diet quality throughout the year. Show less
Merino, J.; Dashti, H.S.; Li, S.X.; Sarnowski, C.; Justice, A.E.; Graff, M.; ... ; Tanaka, T. 2019
Scope Insulin resistance (IR) and inflammation are hallmarks of type 2 diabetes (T2D). The nod-like receptor pyrin domain containing-3 (NLRP3) inflammasome is a metabolic sensor activated by... Show moreScope Insulin resistance (IR) and inflammation are hallmarks of type 2 diabetes (T2D). The nod-like receptor pyrin domain containing-3 (NLRP3) inflammasome is a metabolic sensor activated by saturated fatty acids (SFA) initiating IL-1 beta inflammation and IR. Interactions between SFA intake and NLRP3-related genetic variants may alter T2D risk factors. Methods Meta-analyses of six Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 19 005) tested interactions between SFA and NLRP3-related single-nucleotide polymorphisms (SNPs) and modulation of fasting insulin, fasting glucose, and homeostasis model assessment of insulin resistance. Results SFA interacted with rs12143966, wherein each 1% increase in SFA intake increased insulin by 0.0063 IU mL(-1) (SE +/- 0.002, p = 0.001) per each major (G) allele copy. rs4925663, interacted with SFA (beta +/- SE = -0.0058 +/- 0.002, p = 0.004) to increase insulin by 0.0058 IU mL(-1), per additional copy of the major (C) allele. Both associations are close to the significance threshold (p < 0.0001). rs4925663 causes a missense mutation affecting NLRP3 expression. Conclusion Two NLRP3-related SNPs showed potential interaction with SFA to modulate fasting insulin. Greater dietary SFA intake accentuates T2D risk, which, subject to functional validation, may be further elaborated depending on NLRP3-related genetic variants. Show less
Huang, T.; Wang, T.A.; Zheng, Y.; Ellervik, C.; Li, X.; Gao, M.; ... ; BIRTH-GENE BIG StudyWorking Grp 2019
IMPORTANCE Observational studies have shown associations of birth weight with type 2 diabetes (T2D) and glycemic traits, but it remains unclear whether these associations represent causal... Show moreIMPORTANCE Observational studies have shown associations of birth weight with type 2 diabetes (T2D) and glycemic traits, but it remains unclear whether these associations represent causal associations.OBJECTIVE To test the association of birth weight with T2D and glycemic traits using a mendelian randomization analysis.DESIGN, SETTING, AND PARTICIPANTS This mendelian randomization study used a genetic risk score for birth weight that was constructed with 7 genome-wide significant single-nucleotide polymorphisms. The associations of this score with birth weight and T2D were tested in a mendelian randomization analysis using study-level data. The association of birth weight with T2D was tested using both study-level data (7 single-nucleotide polymorphisms were used as an instrumental variable) and summary-level data from the consortia (43 single-nucleotide polymorphismswere used as an instrumental variable). Data from 180 056 participants from 49 studies were included.MAIN OUTCOMES AND MEASURES Type 2 diabetes and glycemic traits.RESULTS This mendelian randomization analysis included 49 studies with 41 155 patients with T2D and 80 008 control participants from study-level data and 34 840 patients with T2D and 114 981 control participants from summary-level data. Study-level data showed that a 1-SD decrease in birth weight due to the genetic risk score was associated with higher risk of T2D among all participants (odds ratio [OR], 2.10; 95% CI, 1.69-2.61; P=4.03 x 10-5), among European participants (OR, 1.96; 95% CI, 1.42-2.71; P=.04), and among East Asian participants (OR, 1.39; 95% CI, 1.18-1.62; P=.04). Similar results were observed from summary-level analyses. In addition, each 1-SD lower birth weight was associated with 0.189 SD higher fasting glucose concentration (beta=0.189; SE=0.060; P=.002), but not with fasting insulin, 2-hour glucose, or hemoglobin A1c concentration.CONCLUSIONS AND RELEVANCE In this study, a genetic predisposition to lower birth weight was associated with increased risk of T2D and higher fasting glucose concentration, suggesting genetic effects on retarded fetal growth and increased diabetes risk that either are independent of each other or operate through alterations of integrated biological mechanisms. Show less
