Publications by authors named "Ching-Ti Liu"

145 Publications

Polygenic Scores and Parental Predictors: An Adult Height Study Based on the United Kingdom Biobank and the Framingham Heart Study.

Front Genet 2021 21;12:669441. Epub 2021 May 21.

Department of Global Health, School of Public Health, Peking University, Beijing, China.

Human height is a polygenic trait, influenced by a large number of genomic loci. In the pre-genomic era, height prediction was based largely on parental height. More recent predictions of human height have made great strides by integrating genotypic data from large biobanks with improved statistical techniques. Nevertheless, recent studies have not leveraged parental height, an added feature that we hypothesized would offer complementary predictive value. In this study, we assessed the predictive power of polygenic risk scores (PRS) combined with the traditional parental height predictors. Our study analyzed genotypic data and parental height from 1,071 trios from the United Kingdom Biobank and 444 trios from the Framingham Heart Study. We explored a series of statistical models to fully evaluate the performance of several PRS constructed together with parental information and proposed a model we call PRS++ that includes gender, parental height, and PRSs of parents and proband. Our estimate of height with an of ∼0.82 is, to our knowledge, the most accurate estimate yet achieved for predicting human adult height. Without parental information, the from the best PRS-driven model is ∼0.73. In summary, using adult height prediction as an example, we demonstrated that traditional predictors still play important roles and merit integration into the current trends of intensive PRS approaches.
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http://dx.doi.org/10.3389/fgene.2021.669441DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8176283PMC
May 2021

The trans-ancestral genomic architecture of glycemic traits.

Nat Genet 2021 Jun 31;53(6):840-860. Epub 2021 May 31.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
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http://dx.doi.org/10.1038/s41588-021-00852-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610958PMC
June 2021

Genetic variants modify the associations of concentrations of methylmalonic acid, vitamin B-12, vitamin B-6, and folate with bone mineral density.

Am J Clin Nutr 2021 May 8. Epub 2021 May 8.

Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA.

Background: Elevated plasma homocysteine has been found to be associated with an increased risk of osteoporosis, especially hip and vertebral fractures. The plasma concentration of homocysteine is dependent on the activities of several B vitamin-dependent enzymes, such as methylenetetrahydrofolate reductase (MTHFR), methionine synthase (MTR), methionine synthase reductase (MTRR), and cystathionine β-synthase (CBS).

Objectives: We investigated whether genetic variants in some of the genes involved in 1 carbon metabolism modify the association of B vitamin-related measures with bone mineral density (BMD) and strength.

Methods: We measured several B vitamins and biomarkers in participants of the Framingham Offspring Study, and performed analyses of methylmalonic acid (MMA) continuously and <210 nmol/L; pyridoxal-5'-phosphate; vitamin B-12 continuously and ≥258 pmol/L; and folate. The outcomes of interest included areal and volumetric BMD, measured by DXA and quantitative computed tomography (QCT), respectively. We evaluated associations between the bone measures and interactions of single nucleotide polymorphism with a B vitamin or biomarker in Framingham participants (n = 4310 for DXA and n = 3127 for QCT). For analysis of DXA, we validated the association results in the B-PROOF cohort (n = 1072). Bonferroni-corrected locus-wide significant thresholds were defined to account for multiple testing.

Results: The interactions between rs2274976 and vitamin B-12 and rs34671784 and MMA <210 nmol/L were associated with lumbar spine BMD, and the interaction between rs6586281 and vitamin B-12 ≥258 pmol/L was associated with femoral neck BMD. For QCT-derived traits, 62 interactions between genetic variants and B vitamins and biomarkers were identified.

Conclusions: Some genetic variants in the 1-carbon methylation pathway modify the association of B vitamin and biomarker concentrations with bone density and strength.  These interactions require further replication and functional validation for a mechanistic understanding of the role of the 1-carbon metabolism pathway on BMD and risks of fracture.
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http://dx.doi.org/10.1093/ajcn/nqab093DOI Listing
May 2021

Genome-wide association study of neck circumference identifies sex-specific loci independent of generalized adiposity.

Int J Obes (Lond) 2021 Apr 27. Epub 2021 Apr 27.

Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Background/objectives: Neck circumference, an index of upper airway fat, has been suggested to be an important measure of body-fat distribution with unique associations with health outcomes such as obstructive sleep apnea and metabolic disease. This study aims to study the genetic bases of neck circumference.

Methods: We conducted a multi-ethnic genome-wide association study of neck circumference, adjusted and unadjusted for BMI, in up to 15,090 European Ancestry (EA) and African American (AA) individuals. Because sexually dimorphic associations have been observed for anthropometric traits, we conducted both sex-combined and sex-specific analysis.

Results: We identified rs227724 near the Noggin (NOG) gene as a possible quantitative locus for neck circumference in men (N = 8831, P = 1.74 × 10) but not in women (P = 0.08). The association was replicated in men (N = 1554, P = 0.045) in an independent dataset. This locus was previously reported to be associated with human height and with self-reported snoring. We also identified rs13087058 on chromosome 3 as a suggestive locus in sex-combined analysis (N = 15090, P = 2.94 × 10; replication P =0.049). This locus was also associated with electrocardiogram-assessed PR interval and is a cis-expression quantitative locus for the PDZ Domain-containing ring finger 2 (PDZRN3) gene. Both NOG and PDZRN3 interact with members of transforming growth factor-beta superfamily signaling proteins.

Conclusions: Our study suggests that neck circumference may have unique genetic basis independent of BMI.
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http://dx.doi.org/10.1038/s41366-021-00817-2DOI Listing
April 2021

Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure.

Mol Psychiatry 2021 Apr 15. Epub 2021 Apr 15.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 P < 5 × 10), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (P < 5 × 10). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (P = 2 × 10). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (P < 10). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.
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http://dx.doi.org/10.1038/s41380-021-01087-0DOI Listing
April 2021

Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry.

Am J Hum Genet 2021 04 12;108(4):564-582. Epub 2021 Mar 12.

The Charles R. Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.
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http://dx.doi.org/10.1016/j.ajhg.2021.02.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059339PMC
April 2021

Detecting differentially methylated regions with multiple distinct associations.

Epigenomics 2021 Mar 1;13(6):451-464. Epub 2021 Mar 1.

Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA.

We evaluated five methods for detecting differentially methylated regions (DMRs): DMRcate, comb-p, seqlm, GlobalP and dmrff. We used a simulation study and real data analysis to evaluate performance. Additionally, we evaluated the use of an ancestry-matched reference cohort to estimate correlations between CpG sites in cord blood. Several methods had inflated Type I error, which increased at more stringent significant levels. In power simulations with 1-2 causal CpG sites with the same direction of effect, dmrff was consistently among the most powerful methods. This study illustrates the need for more thorough simulation studies when evaluating novel methods. More work must be done to develop methods with well-controlled Type I error that do not require individual-level data.
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http://dx.doi.org/10.2217/epi-2020-0344DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8023344PMC
March 2021

Small Dense Low-Density Lipoprotein Cholesterol Is the Most Atherogenic Lipoprotein Parameter in the Prospective Framingham Offspring Study.

J Am Heart Assoc 2021 Feb 15;10(5):e019140. Epub 2021 Feb 15.

Cardiovascular Nutrition Laboratory Jean Mayer United States Department of Agriculture Human Nutrition Research Center on Aging at Tufts University Boston MA.

Background Elevated plasma levels of direct low-density lipoprotein cholesterol (LDL-C), small dense LDL-C (sdLDL-C), low-density lipoprotein (LDL) triglycerides, triglycerides, triglyceride-rich lipoprotein cholesterol, remnant lipoprotein particle cholesterol, and lipoprotein(a) have all been associated with incident atherosclerotic cardiovascular disease (ASCVD). Our goal was to assess which parameters were most strongly associated with ASCVD risk. Methods and Results Plasma total cholesterol, triglycerides, high-density lipoprotein cholesterol, direct LDL-C, sdLDL-C, LDL triglycerides, remnant lipoprotein particle cholesterol, triglyceride-rich lipoprotein cholesterol, and lipoprotein(a) were measured using standardized automated analysis (coefficients of variation, <5.0%) in samples from 3094 fasting subjects free of ASCVD. Of these subjects, 20.2% developed ASCVD over 16 years. On univariate analysis, all ASCVD risk factors were significantly associated with incident ASCVD, as well as the following specialized lipoprotein parameters: sdLDL-C, LDL triglycerides, triglycerides, triglyceride-rich lipoprotein cholesterol, remnant lipoprotein particle cholesterol, and direct LDL-C. Only sdLDL-C, direct LDL-C, and lipoprotein(a) were significant on multivariate analysis and net reclassification after adjustment for standard risk factors (age, sex, hypertension, diabetes mellitus, smoking, total cholesterol, and high-density lipoprotein cholesterol). Using the pooled cohort equation, many specialized lipoprotein parameters individually added significant information, but no parameter added significant information once sdLDL-C (hazard ratio, 1.42; <0.0001) was in the model. These results for sdLDL-C were confirmed by adjusted discordance analysis versus calculated non-high-density lipoprotein cholesterol, in contrast to LDL triglycerides. Conclusions sdLDL-C, direct LDL-C, and lipoprotein(a) all contributed significantly to ASCVD risk on multivariate analysis, but no parameter added significant risk information to the pooled cohort equation once sdLDL-C was in the model. Our data indicate that small dense LDL is the most atherogenic lipoprotein parameter.
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http://dx.doi.org/10.1161/JAHA.120.019140DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8174280PMC
February 2021

Lifestyle Risk Score: handling missingness of individual lifestyle components in meta-analysis of gene-by-lifestyle interactions.

Eur J Hum Genet 2021 May 26;29(5):839-850. Epub 2021 Jan 26.

Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.

Recent studies consider lifestyle risk score (LRS), an aggregation of multiple lifestyle exposures, in identifying association of gene-lifestyle interaction with disease traits. However, not all cohorts have data on all lifestyle factors, leading to increased heterogeneity in the environmental exposure in collaborative meta-analyses. We compared and evaluated four approaches (Naïve, Safe, Complete and Moderator Approaches) to handle the missingness in LRS-stratified meta-analyses under various scenarios. Compared to "benchmark" results with all lifestyle factors available for all cohorts, the Complete Approach, which included only cohorts with all lifestyle components, was underpowered due to lower sample size, and the Naïve Approach, which utilized all available data and ignored the missingness, was slightly inflated. The Safe Approach, which used all data in LRS-exposed group and only included cohorts with all lifestyle factors available in the LRS-unexposed group, and the Moderator Approach, which handled missingness via moderator meta-regression, were both slightly conservative and yielded almost identical p values. We also evaluated the performance of the Safe Approach under different scenarios. We observed that the larger the proportion of cohorts without missingness included, the more accurate the results compared to "benchmark" results. In conclusion, we generally recommend the Safe Approach, a straightforward and non-inflated approach, to handle heterogeneity among cohorts in the LRS based genome-wide interaction meta-analyses.
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http://dx.doi.org/10.1038/s41431-021-00808-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8110957PMC
May 2021

Metabolomics Insights into Osteoporosis Through Association With Bone Mineral Density.

J Bone Miner Res 2021 Apr 2;36(4):729-738. Epub 2021 Feb 2.

Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.

Osteoporosis, a disease characterized by low bone mineral density (BMD), increases the risk for fractures. Conventional risk factors alone do not completely explain measured BMD or osteoporotic fracture risk. Metabolomics may provide additional information. We aim to identify BMD-associated metabolomic markers that are predictive of fracture risk. We assessed 209 plasma metabolites by liquid chromatography with tandem mass spectrometry (LC-MS/MS) in 1552 Framingham Offspring Study participants, and measured femoral neck (FN) and lumbar spine (LS) BMD 2 to 10 years later using dual-energy X-ray absorptiometry. We assessed osteoporotic fractures up to 27-year follow-up after metabolomic profiling. We identified 27 metabolites associated with FN-BMD or LS-BMD by LASSO regression with internal validation. Incorporating selected metabolites significantly improved the prediction and the classification of osteoporotic fracture risk beyond conventional risk factors (area under the curve [AUC] = 0.74 for the model with identified metabolites and risk factors versus AUC = 0.70 with risk factors alone, p = .001; net reclassification index = 0.07, p = .03). We replicated significant improvement in fracture prediction by incorporating selected metabolites in 634 participants from the Hong Kong Osteoporosis Study (HKOS). The glycine, serine, and threonine metabolism pathway (including four identified metabolites: creatine, dimethylglycine, glycine, and serine) was significantly enriched (false discovery rate [FDR] p value = .028). Furthermore, three causally related metabolites (glycine, phosphatidylcholine [PC], and triacylglycerol [TAG]) were negatively associated with FN-BMD, whereas PC and TAG were negatively associated with LS-BMD through Mendelian randomization analysis. In summary, metabolites associated with BMD are helpful in osteoporotic fracture risk prediction. Potential causal mechanisms explaining the three metabolites on BMD are worthy of further experimental validation. Our findings may provide novel insights into the pathogenesis of osteoporosis. © 2021 American Society for Bone and Mineral Research (ASBMR).
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http://dx.doi.org/10.1002/jbmr.4240DOI Listing
April 2021

A Meta-Analysis of the Transferability of Bone Mineral Density Genetic Loci Associations From European to African Ancestry Populations.

J Bone Miner Res 2021 Mar 18;36(3):469-479. Epub 2020 Dec 18.

Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA.

Genetic studies of bone mineral density (BMD) largely have been conducted in European populations. We therefore conducted a meta-analysis of six independent African ancestry cohorts to determine whether previously reported BMD loci identified in European populations were transferable to African ancestry populations. We included nearly 5000 individuals with both genetic data and assessments of BMD. Genotype imputation was conducted using the 1000G reference panel. We assessed single-nucleotide polymorphism (SNP) associations with femoral neck and lumbar spine BMD in each cohort separately, then combined results in fixed effects (or random effects if study heterogeneity was high, I index >60) inverse variance weighted meta-analyses. In secondary analyses, we conducted locus-based analyses of rare variants using SKAT-O. Mean age ranged from 12 to 68 years. One cohort included only men and another cohort included only women; the proportion of women in the other four cohorts ranged from 52% to 63%. Of 56 BMD loci tested, one locus, 6q25 (C6orf97, p = 8.87 × 10 ), was associated with lumbar spine BMD and two loci, 7q21 (SLC25A13, p = 2.84 × 10 ) and 7q31 (WNT16, p = 2.96 × 10 ), were associated with femoral neck BMD. Effects were in the same direction as previously reported in European ancestry studies and met a Bonferroni-adjusted p value threshold, the criteria for transferability to African ancestry populations. We also found associations that met locus-specific Bonferroni-adjusted p value thresholds in 11q13 (LRP5, p < 2.23 × 10 ), 11q14 (DCDC5, p < 5.35 × 10 ), and 17p13 (SMG6, p < 6.78 × 10 ) that were not tagged by European ancestry index SNPs. Rare single-nucleotide variants in AKAP11 (p = 2.32 × 10 ), MBL2 (p = 4.09 × 10 ), MEPE (p = 3.15 × 10 ), SLC25A13 (p = 3.03 × 10 ), STARD3NL (p = 3.35 × 10 ), and TNFRSF11A (p = 3.18 × 10 ) were also associated with BMD. The majority of known BMD loci were not transferable. Larger genetic studies of BMD in African ancestry populations will be needed to overcome limitations in statistical power and to identify both other loci that are transferable across populations and novel population-specific variants. © 2020 American Society for Bone and Mineral Research (ASBMR).
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http://dx.doi.org/10.1002/jbmr.4220DOI Listing
March 2021

Hepatic Fibrosis Associates With Multiple Cardiometabolic Disease Risk Factors: The Framingham Heart Study.

Hepatology 2021 Feb 6;73(2):548-559. Epub 2021 Feb 6.

Evans Department of Medicine, Whitaker Cardiovascular Institute and Cardiology Section, Boston University School of Medicine, Boston, MA.

Background And Aims: NAFLD is increasing in prevalence and will soon be the most common chronic liver disease. Liver stiffness, as assessed by vibration-controlled transient elastography (VCTE), correlates with hepatic fibrosis, an important predictor of liver-related and all-cause mortality. Although liver fat is associated with cardiovascular risk factors, the association between hepatic fibrosis and cardiovascular risk factors is less clear.

Approach And Results: We performed VCTE, assessing controlled attenuation parameter (CAP; measure of steatosis) and liver stiffness measurement (LSM) in 3,276 Framingham Heart Study adult participants (53.9% women, mean age 54.3 ± 9.1 years) presenting for a routine study visit. We performed multivariable-adjusted logistic regression models to determine the association between LSM and obesity-related, vascular-related, glucose-related, and cholesterol-related cardiovascular risk factors. The prevalence of hepatic steatosis (CAP ≥ 290 dB/m) was 28.8%, and 8.8% had hepatic fibrosis (LSM ≥ 8.2 kPa). Hepatic fibrosis was associated with multiple cardiovascular risk factors, including increased odds of obesity (OR, 1.82; 95% CI, 1.35-2.47), metabolic syndrome (OR, 1.49; 95% CI 1.10-2.01), diabetes (OR, 2.67; 95% CI, 1.21-3.75), hypertension (OR, 1.52; 95% CI, 1.15-1.99), and low high-density lipoprotein cholesterol (OR, 1.47; 95% CI, 1.09-1.98), after adjustment for age, sex, smoking status, alcohol drinks/week, physical activity index, aminotransferases, and CAP.

Conclusions: In our community-based cohort, VCTE-defined hepatic fibrosis was associated with multiple cardiovascular risk factors, including obesity, metabolic syndrome, diabetes, hypertension, and high-density lipoprotein cholesterol, even after accounting for covariates and CAP. Additional longitudinal studies are needed to determine if hepatic fibrosis contributes to incident cardiovascular disease risk factors or events.
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http://dx.doi.org/10.1002/hep.31608DOI Listing
February 2021

Associations of staple food consumption and types of cooking oil with waist circumference and body mass index in older Chinese men and women: a panel analysis.

Int Health 2021 02;13(2):178-187

Boston University, School of Public Health, Department of Biostatistics, Boston, MA 02118, USA.

Background: The dietary landscape has changed rapidly in China in the past few decades. This research investigates the associations of older adults' choices and consumption of staple foods and cooking oils with obesity-related measurements.

Methods: Panel data were extracted from the Chinese Longitudinal Health Longevity Survey from 3253 older participants with 6506 observations. Ordinary least squares and ordered logistic regression models were estimated with the outcomes of obesity determined by waist circumference (WC) and body mass index (BMI), respectively.

Results: Older men who consumed wheat had wider WCs (β=2.84 [95% confidence interval {CI} 1.55 to 4.13], p<0.01) and higher BMIs (adjusted odds ratio 1.74 [95% CI 1.40 to 2.17], p<0.01) than those who preferred rice. Female participants who used animal-based cooking oil had lower WCs and BMIs than their counterparts who consumed vegetable-based cooking oil. Increased consumption of staple foods was associated with increased rates of obesity in both sexes.

Conclusion: Dieticians and nutritionists should design appropriate dietary plans to help reduce obesity and chronic diseases among older Chinese adults. Further clinical trials are needed to continue investigating this topic.
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http://dx.doi.org/10.1093/inthealth/ihaa074DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902270PMC
February 2021

Methylome-wide association study of central adiposity implicates genes involved in immune and endocrine systems.

Epigenomics 2020 09 9;12(17):1483-1499. Epub 2020 Sep 9.

Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

We conducted a methylome-wide association study to examine associations between DNA methylation in whole blood and central adiposity and body fat distribution, measured as waist circumference, waist-to-hip ratio and waist-to-height ratio adjusted for body mass index, in 2684 African-American adults in the Atherosclerosis Risk in Communities study. We validated significantly associated cytosine-phosphate-guanine methylation sites (CpGs) among adults using the Women's Health Initiative and Framingham Heart Study participants (combined n = 5743) and generalized associations in adolescents from The Raine Study (n = 820). We identified 11 CpGs that were robustly associated with one or more central adiposity trait in adults and two in adolescents, including CpG site associations near , ,  and that had not previously been associated with obesity-related traits.
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http://dx.doi.org/10.2217/epi-2019-0276DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923253PMC
September 2020

Efficient gene-environment interaction tests for large biobank-scale sequencing studies.

Genet Epidemiol 2020 11 30;44(8):908-923. Epub 2020 Aug 30.

Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas.

Complex human diseases are affected by genetic and environmental risk factors and their interactions. Gene-environment interaction (GEI) tests for aggregate genetic variant sets have been developed in recent years. However, existing statistical methods become rate limiting for large biobank-scale sequencing studies with correlated samples. We propose efficient Mixed-model Association tests for GEne-Environment interactions (MAGEE), for testing GEI between an aggregate variant set and environmental exposures on quantitative and binary traits in large-scale sequencing studies with related individuals. Joint tests for the aggregate genetic main effects and GEI effects are also developed. A null generalized linear mixed model adjusting for covariates but without any genetic effects is fit only once in a whole genome GEI analysis, thereby vastly reducing the overall computational burden. Score tests for variant sets are performed as a combination of genetic burden and variance component tests by accounting for the genetic main effects using matrix projections. The computational complexity is dramatically reduced in a whole genome GEI analysis, which makes MAGEE scalable to hundreds of thousands of individuals. We applied MAGEE to the exome sequencing data of 41,144 related individuals from the UK Biobank, and the analysis of 18,970 protein coding genes finished within 10.4 CPU hours.
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http://dx.doi.org/10.1002/gepi.22351DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7754763PMC
November 2020

Evaluation of population stratification adjustment using genome-wide or exonic variants.

Genet Epidemiol 2020 10 30;44(7):702-716. Epub 2020 Jun 30.

Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts.

Population stratification may cause an inflated type-I error and spurious association when assessing the association between genetic variations with an outcome. Many genetic association studies are now using exonic variants, which captures only 1% of the genome, however, population stratification adjustments have not been evaluated in the context of exonic variants. We compare the performance of two established approaches: principal components analysis (PCA) and mixed-effects models and assess the utility of genome-wide (GW) and exonic variants, by simulation and using a data set from the Framingham Heart Study. Our results illustrate that although the PCs and genetic relationship matrices computed by GW and exonic markers are different, the type-I error rate of association tests for common variants with additive effect appear to be properly controlled in the presence of population stratification. In addition, by considering single nucleotide variants (SNVs) that have different levels of confounding by population stratification, we also compare the power across multiple association approaches to account for population stratification such as PC-based corrections and mixed-effects models. We find that while these two methods achieve a similar power for SNVs that have a low or medium level of confounding by population stratification, mixed-effects model can reach a higher power for SNVs highly confounded by population stratification.
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http://dx.doi.org/10.1002/gepi.22332DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722041PMC
October 2020

Regional and Geographical Disparities in Body Mass Index (BMI) Among Chinese Older Adults: The Chinese Longitudinal Healthy Longevity Survey.

J Appl Gerontol 2020 Jun 15:733464820930963. Epub 2020 Jun 15.

National Tsing Hua University, Hsinchu City.

This study examined the regional and geographical disparities in body mass index (BMI) among Chinese older adults. Using panel data from the Chinese Longitudinal Healthy Longevity Survey, participants included 3,740 older adults (age ≥ 65 years) who answered all three waves of the survey (2009-2014). Sex-stratified and multistate Cox regression was used to examine the disparities in BMI change. Results showed that both older males and older females who resided in the central-south had lower rates of weight change from nonobese to obese, compared with those from the east. Older females from urban regions had higher rate of weight change from nonobese to obese, compared with rural participants (hazard ratio [HR]: 1.35, 95% confidence interval [CI] = [1.13, 1.60]; < .01). However, there were no disparities between urban and rural areas among older males ( > .05). These results provided practical implications for regional and geographical disparities in BMI among Chinese older adults.
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http://dx.doi.org/10.1177/0733464820930963DOI Listing
June 2020

Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels.

Circ Genom Precis Med 2020 08 8;13(4):e002772. Epub 2020 Jun 8.

Department of Epidemiology, School of Public Health (L.F.B., J.A.S., W.Z., S.L.R.K.), University of Michigan, Ann Arbor, MI.

Background: Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels.

Methods: In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered.

Results: We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (, , , , , , , and ) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (=6.65×10 for the interaction test) and replicated at nominal significance level (=0.013) in .

Conclusions: In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.
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http://dx.doi.org/10.1161/CIRCGEN.119.002772DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442680PMC
August 2020

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose.

PLoS One 2020 7;15(5):e0230815. Epub 2020 May 7.

Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America.

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 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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0230815PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205201PMC
August 2020

Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci.

Mol Psychiatry 2020 May 5. Epub 2020 May 5.

Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA.

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.
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http://dx.doi.org/10.1038/s41380-020-0719-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641978PMC
May 2020

Searching for parent-of-origin effects on cardiometabolic traits in imprinted genomic regions.

Eur J Hum Genet 2020 05 2;28(5):646-655. Epub 2020 Jan 2.

Braun School of Public Health, The Hebrew University of Jerusalem, 99112102, Jerusalem, Israel.

Cardiometabolic traits pose a major global public health burden. Large-scale genome-wide association studies (GWAS) have identified multiple loci accounting for up to 30% of the genetic variance in complex traits such as cardiometabolic traits. However, the contribution of parent-of-origin effects (POEs) to complex traits has been largely ignored in GWAS. Family-based studies enable the assessment of POEs in genetic association analyses. We investigated POEs on a range of complex traits in 3 family-based studies. The discovery phase was carried out in large pedigrees from the Kibbutzim Family Study (n = 901 individuals) and in 872 parent-offspring trios from the Jerusalem Perinatal Study. Focusing on imprinted genomic regions, we examined parent-specific associations with 12 complex traits (i.e., body-size, blood pressure, lipids), mostly cardiometabolic risk traits. Forty five of the 11,967 SNPs initially found to have POE were evaluated for replication (p value < 1 × 10) in Framingham Heart Study families (max n = 8000 individuals). Three common variants yielded evidence of POE in the meta-analysis. Two variants, located on chr6 in the HLA region, showed a paternal effect on height (rs1042136: β = -0.023, p value = 1.5 × 10 and rs1431403: β = -0.011, p value = 5.4 × 10). The corresponding maternally-derived effects were statistically nonsignificant. The variant rs9332053, located on chr13 in RCBTB2 gene, demonstrated a maternal effect on hip circumference (β = -4.24, p value = 9.6 × 10; β = 1.29, p value = 0.23). These findings provide evidence for the utility of incorporating POEs into association studies of cardiometabolic traits, especially anthropometric traits. The study highlights the benefits of using family-based data for deciphering the genetic architecture of complex traits.
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http://dx.doi.org/10.1038/s41431-019-0568-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7170899PMC
May 2020

A unified method for rare variant analysis of gene-environment interactions.

Stat Med 2020 03 4;39(6):801-813. Epub 2019 Dec 4.

Department of Biostatistics, Boston University, Boston, Massachusetts.

Advanced technology in whole-genome sequencing has offered the opportunity to comprehensively investigate the genetic contribution, particularly rare variants, to complex traits. Several region-based tests have been developed to jointly model the marginal effect of rare variants, but methods to detect gene-environment (GE) interactions are underdeveloped. Identifying the modification effects of environmental factors on genetic risk poses a considerable challenge. To tackle this challenge, we develop a method to detect GE interactions for rare variants using generalized linear mixed effect model. The proposed method can accommodate either binary or continuous traits in related or unrelated samples. Under this model, genetic main effects, GE interactions, and sample relatedness are modeled as random effects. We adopt a kernel-based method to leverage the joint information across rare variants and implement variance component score tests to reduce the computational burden. Our simulation studies of continuous and binary traits show that the proposed method maintains correct type I error rates and appropriate power under various scenarios, such as genotype main effects and GE interaction effects in opposite directions and varying the proportion of causal variants in the model. We apply our method in the Framingham Heart Study to test GE interaction of smoking on body mass index or overweight status and replicate the Cholinergic Receptor Nicotinic Beta 4 gene association reported in previous large consortium meta-analysis of single nucleotide polymorphism-smoking interaction. Our proposed set-based GE test is computationally efficient and is applicable to both binary and continuous phenotypes, while appropriately accounting for familial or cryptic relatedness.
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http://dx.doi.org/10.1002/sim.8446DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7261513PMC
March 2020

Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

Nat Commun 2019 11 12;10(1):5121. Epub 2019 Nov 12.

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands.

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
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http://dx.doi.org/10.1038/s41467-019-12958-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851116PMC
November 2019

Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program.

Am J Hum Genet 2019 10 26;105(4):706-718. Epub 2019 Sep 26.

National Heart, Lung, and Blood Institute and Boston University's Framingham Heart Study, Framingham MA 01702, USA; Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA.

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.
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http://dx.doi.org/10.1016/j.ajhg.2019.08.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817529PMC
October 2019

Genome-Wide Association Study of Apparent Treatment-Resistant Hypertension in the CHARGE Consortium: The CHARGE Pharmacogenetics Working Group.

Am J Hypertens 2019 11;32(12):1146-1153

Robertson Center for Biostatistics, University of Glasgow, Glasgow, UK.

Background: Only a handful of genetic discovery efforts in apparent treatment-resistant hypertension (aTRH) have been described.

Methods: We conducted a case-control genome-wide association study of aTRH among persons treated for hypertension, using data from 10 cohorts of European ancestry (EA) and 5 cohorts of African ancestry (AA). Cases were treated with 3 different antihypertensive medication classes and had blood pressure (BP) above goal (systolic BP ≥ 140 mm Hg and/or diastolic BP ≥ 90 mm Hg) or 4 or more medication classes regardless of BP control (nEA = 931, nAA = 228). Both a normotensive control group and a treatment-responsive control group were considered in separate analyses. Normotensive controls were untreated (nEA = 14,210, nAA = 2,480) and had systolic BP/diastolic BP < 140/90 mm Hg. Treatment-responsive controls (nEA = 5,266, nAA = 1,817) had BP at goal (<140/90 mm Hg), while treated with one antihypertensive medication class. Individual cohorts used logistic regression with adjustment for age, sex, study site, and principal components for ancestry to examine the association of single-nucleotide polymorphisms with case-control status. Inverse variance-weighted fixed-effects meta-analyses were carried out using METAL.

Results: The known hypertension locus, CASZ1, was a top finding among EAs (P = 1.1 × 10-8) and in the race-combined analysis (P = 1.5 × 10-9) using the normotensive control group (rs12046278, odds ratio = 0.71 (95% confidence interval: 0.6-0.8)). Single-nucleotide polymorphisms in this locus were robustly replicated in the Million Veterans Program (MVP) study in consideration of a treatment-responsive control group. There were no statistically significant findings for the discovery analyses including treatment-responsive controls.

Conclusion: This genomic discovery effort for aTRH identified CASZ1 as an aTRH risk locus.
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http://dx.doi.org/10.1093/ajh/hpz150DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856621PMC
November 2019

Associations of alcohol consumption status with activities of daily living among older adults in China.

J Ethn Subst Abuse 2019 Sep 18:1-16. Epub 2019 Sep 18.

Boston University , Boston , MA.

With the rapid growth of the elderly population and public health challenges in China, concerns arise related to disability associated with activities of daily living (ADLs) and alcohol consumption status. This study assesses the relationships of alcohol consumption status with basic daily activities among Chinese older adults. A total of 5,133 participants aged 60 years or above from three waves of the Chinese Longitudinal Healthy Longevity Survey (2009, 2012, and 2014) were analyzed. Independent ADL items included bathing, dressing, toileting, indoor moving, continence, and feeding (without others' assistance). Multilevel ordered logistic regression model estimation was used to examine the results of total scores based on the Katz index. Multilevel logistic regression models also were estimated to study each index item separately to examine differences across each of the six ADLs. Additional confirmatory factor analysis (CFA) was performed to examine the validity of the index. Preliminary CFA showed that most items had good factor loadings (>0.700), except for continence (0.256) and feeding (0.481). Based on the ordered regression model, former (AOR = 0.412, 95% CI: 0.294, 0.579,  < 0.001) and non-alcohol consumption (AOR = 0.598, 95% CI: 0.447, 0.800,  < 0.001) were negatively associated with the total score. Non-alcohol consumption status was negatively associated with ADL items separately (all s < 0.05), with the exceptions of continence and feeding. Alcohol consumption may be associated with Chinese older adults' better ADLs. However, further clinical or experimental trials are needed to examine the impact of alcohol consumption on older adults' ADLs.
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http://dx.doi.org/10.1080/15332640.2019.1664961DOI Listing
September 2019

Potential Interplay between Dietary Saturated Fats and Genetic Variants of the NLRP3 Inflammasome to Modulate Insulin Resistance and Diabetes Risk: Insights from a Meta-Analysis of 19 005 Individuals.

Mol Nutr Food Res 2019 11 12;63(22):e1900226. Epub 2019 Sep 12.

Jean Mayer USDA Human Nutrition Research Centre on Aging, Tufts University, Boston, MA, 02111, USA.

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 saturated fatty acids (SFA) initiating IL-1β 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 (SE ± 0.002, p = 0.001) per each major (G) allele copy. rs4925663, interacted with SFA (β ± SE = -0.0058 ± 0.002, p = 0.004) to increase insulin by 0.0058 IU mL , 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.
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http://dx.doi.org/10.1002/mnfr.201900226DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864231PMC
November 2019

Quality of dietary fat and genetic risk of type 2 diabetes: individual participant data meta-analysis.

BMJ 2019 07 25;366:l4292. Epub 2019 Jul 25.

Objective: To investigate whether the genetic burden of type 2 diabetes modifies the association between the quality of dietary fat and the incidence of type 2 diabetes.

Design: Individual participant data meta-analysis.

Data Sources: Eligible prospective cohort studies were systematically sourced from studies published between January 1970 and February 2017 through electronic searches in major medical databases (Medline, Embase, and Scopus) and discussion with investigators.

Review Methods: Data from cohort studies or multicohort consortia with available genome-wide genetic data and information about the quality of dietary fat and the incidence of type 2 diabetes in participants of European descent was sought. Prospective cohorts that had accrued five or more years of follow-up were included. The type 2 diabetes genetic risk profile was characterized by a 68-variant polygenic risk score weighted by published effect sizes. Diet was recorded by using validated cohort-specific dietary assessment tools. Outcome measures were summary adjusted hazard ratios of incident type 2 diabetes for polygenic risk score, isocaloric replacement of carbohydrate (refined starch and sugars) with types of fat, and the interaction of types of fat with polygenic risk score.

Results: Of 102 305 participants from 15 prospective cohort studies, 20 015 type 2 diabetes cases were documented after a median follow-up of 12 years (interquartile range 9.4-14.2). The hazard ratio of type 2 diabetes per increment of 10 risk alleles in the polygenic risk score was 1.64 (95% confidence interval 1.54 to 1.75, I=7.1%, τ=0.003). The increase of polyunsaturated fat and total omega 6 polyunsaturated fat intake in place of carbohydrate was associated with a lower risk of type 2 diabetes, with hazard ratios of 0.90 (0.82 to 0.98, I=18.0%, τ=0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I=58.8%, τ=0.001; per increment of 1 g/d), respectively. Increasing monounsaturated fat in place of carbohydrate was associated with a higher risk of type 2 diabetes (hazard ratio 1.10, 95% confidence interval 1.01 to 1.19, I=25.9%, τ=0.006; per 5% of energy). Evidence of small study effects was detected for the overall association of polyunsaturated fat with the risk of type 2 diabetes, but not for the omega 6 polyunsaturated fat and monounsaturated fat associations. Significant interactions between dietary fat and polygenic risk score on the risk of type 2 diabetes (P>0.05 for interaction) were not observed.

Conclusions: These data indicate that genetic burden and the quality of dietary fat are each associated with the incidence of type 2 diabetes. The findings do not support tailoring recommendations on the quality of dietary fat to individual type 2 diabetes genetic risk profiles for the primary prevention of type 2 diabetes, and suggest that dietary fat is associated with the risk of type 2 diabetes across the spectrum of type 2 diabetes genetic risk.
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http://dx.doi.org/10.1136/bmj.l4292DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6652797PMC
July 2019

Examining the Associations of Smoking Behavior and Obesity Among Older Adults in China: Should We Consider Food Consumption Behaviors?

J Aging Health 2020 Aug-Sep;32(7-8):904-915. Epub 2019 Jul 24.

Boston University, MA, USA.

This research investigates the associations between smoking frequency and body mass index (BMI) among older adults in China with and without the inclusion of food consumption behaviors. Applying three waves of the Chinese Longitudinal Healthy Longevity Survey (2009, 2012, and 2014), with 12,312 observations from 4,104 participants, gender-stratified panel ordered logistic regressions were performed. Food consumption included intake frequency and types of fruits, vegetables, staple food, cooking oil, and meat. Among male older adults, more frequent smoking behavior was associated with lower BMI with the inclusion of food consumption behaviors. However, more frequent smoking behavior was not associated with BMI among female participants with the inclusion of food consumption behaviors. Former smoking status was not associated with BMI in all models. The findings suggest the need of food consumption behaviors when researchers study the associations between smoking frequency and obesity. Gender gaps also should be considered.
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http://dx.doi.org/10.1177/0898264319862417DOI Listing
April 2021

Genome-wide Association Study of Change in Fasting Glucose over time in 13,807 non-diabetic European Ancestry Individuals.

Sci Rep 2019 07 1;9(1):9439. Epub 2019 Jul 1.

Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.

Type 2 diabetes (T2D) affects the health of millions of people worldwide. The identification of genetic determinants associated with changes in glycemia over time might illuminate biological features that precede the development of T2D. Here we conducted a genome-wide association study of longitudinal fasting glucose changes in up to 13,807 non-diabetic individuals of European descent from nine cohorts. Fasting glucose change over time was defined as the slope of the line defined by multiple fasting glucose measurements obtained over up to 14 years of observation. We tested for associations of genetic variants with inverse-normal transformed fasting glucose change over time adjusting for age at baseline, sex, and principal components of genetic variation. We found no genome-wide significant association (P < 5 × 10) with fasting glucose change over time. Seven loci previously associated with T2D, fasting glucose or HbA1c were nominally (P < 0.05) associated with fasting glucose change over time. Limited power influences unambiguous interpretation, but these data suggest that genetic effects on fasting glucose change over time are likely to be small. A public version of the data provides a genomic resource to combine with future studies to evaluate shared genetic links with T2D and other metabolic risk traits.
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http://dx.doi.org/10.1038/s41598-019-45823-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602949PMC
July 2019