The association between body mass index and metabolite response to a liquid mixed meal challenge: a Mendelian randomization study.

BACKGROUND: Metabolite abundance is a dynamic trait that varies in response to environmental stimuli and phenotypic traits, such as food consumption and body mass index (BMI, kg/m2). OBJECTIVES: In this study, we used the Netherlands Epidemiology of Obesity (NEO) study data to identify observational and causal associations between BMI and metabolite response to a liquid meal. METHODS: A liquid meal challenge was performed, and Nightingale Health metabolite profiles were collected in 5744 NEO participants. Observational and one-sample Mendelian randomization (MR) analysis were conducted to estimate the effect of BMI on metabolites (n = 229) in the fasting, postprandial, and response (or change in abundance) states. RESULTS: We observed 473 associations with BMI (175 fasting, 188 postprandial, and 110 response) in observational analyses. In MR analyses, we observed 20 metabolite traits (5 fasting, 12 postprandial, and 3 response) to be associated with BMI. MR associations included the glucogenic amino acid alanine, which was inversely associated with BMI in the response state (ß: -0.081; SE: 0.023; P = 5.91 × 10-4), suggesting that as alanine increased in postprandial abundance, that increase was attenuated with increasing BMI. CONCLUSIONS: Overall, this study showed that MR estimates were strongly correlated with observational effect estimates, suggesting that the broad associations seen between BMI and metabolite variation has a causal underpinning. Specific effects in previously unassessed postprandial and response states are detected, and these may likely mark novel life course risk exposures driven by regular nutrition.

[Soft tissue infections]. / Wekedeleninfecties.

Soft tissue infections are common, but can be difficult to diagnose and manage. In this article, the classification of soft tissue infections is discussed, as well as the diagnostic possibilities and treatment options. Furthermore, the management of recurrent infections and necrotizing soft tissue infections are discussed. The added value of compression therapy is reviewed in more detail.

Genome-wide characterization of circulating metabolic biomarkers.

Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism1-7. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases8-11. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases.

Dutch GPs' perspectives on addressing obesity: a qualitative study.

BACKGROUND: Early diagnosis and treatment of obesity in primary care may help to tackle the obesity pandemic. Nonetheless, GPs frequently fail to address obesity and demonstrate limited adherence to guidelines. AIM: To explore Dutch GPs' perspectives on addressing obesity regarding the following three target behaviours: discussing weight; diagnosing; and referring patients with obesity. DESIGN & SETTING: A qualitative focus group study with Dutch GPs. METHOD: Six focus groups were conducted with a purposive sample of 21 GPs. Thematic analysis was performed using deductive coding, according to the Theoretical Domains Framework (TDF). RESULTS: For discussing weight, the main barriers identified were a presented complaint unrelated to obesity (environmental context and resources), concerns about a negative response from the patient (beliefs about consequences), and worries about obesity being a sensitive subject to discuss (emotions). A long-term trustworthy relationship (social influences) facilitated discussing weight. For diagnosing patients with obesity, the main barriers were related to resources; for example, lack of (appropriate) measuring equipment and time (environmental context and resources). For referring patients with obesity, the main barriers were no referral options nearby (environmental context and resources), and doubts about the positive effects of the referral on weight change (beliefs about consequences). CONCLUSION: Different barriers for discussing weight, diagnosing, and referring patients with obesity were identified, underscoring the importance for tailored interventions to these specific behaviours. Improving knowledge and skills of GPs seems insufficient as this study showed that particular attention should be paid to establishing long-term relationships, addressing GPs' beliefs about consequences, and creating a supportive environment with sufficient time and resources.

Bone mineral density loci specific to the skull portray potential pleiotropic effects on craniosynostosis.

Skull bone mineral density (SK-BMD) provides a suitable trait for the discovery of key genes in bone biology, particularly to intramembranous ossification, not captured at other skeletal sites. We perform a genome-wide association meta-analysis (n ~ 43,800) of SK-BMD, identifying 59 loci, collectively explaining 12.5% of the trait variance. Association signals cluster within gene-sets involved in skeletal development and osteoporosis. Among the four novel loci (ZIC1, PRKAR1A, AZIN1/ATP6V1C1, GLRX3), there are factors implicated in intramembranous ossification and as we show, inherent to craniosynostosis processes. Functional follow-up in zebrafish confirms the importance of ZIC1 on cranial suture patterning. Likewise, we observe abnormal cranial bone initiation that culminates in ectopic sutures and reduced BMD in mosaic atp6v1c1 knockouts. Mosaic prkar1a knockouts present asymmetric bone growth and, conversely, elevated BMD. In light of this evidence linking SK-BMD loci to craniofacial abnormalities, our study provides new insight into the pathophysiology, diagnosis and treatment of skeletal diseases.

Circulating metabolites modulated by diet are associated with depression.

Metabolome reflects the interplay of genome and exposome at molecular level and thus can provide deep insights into the pathogenesis of a complex disease like major depression. To identify metabolites associated with depression we performed a metabolome-wide association analysis in 13,596 participants from five European population-based cohorts characterized for depression, and circulating metabolites using ultra high-performance liquid chromatography/tandem accurate mass spectrometry (UHPLC/MS/MS) based Metabolon platform. We tested 806 metabolites covering a wide range of biochemical processes including those involved in lipid, amino-acid, energy, carbohydrate, xenobiotic and vitamin metabolism for their association with depression. In a conservative model adjusting for life style factors and cardiovascular and antidepressant medication use we identified 8 metabolites, including 6 novel, significantly associated with depression. In individuals with depression, increased levels of retinol (vitamin A), 1-palmitoyl-2-palmitoleoyl-GPC (16:0/16:1) (lecithin) and mannitol/sorbitol and lower levels of hippurate, 4-hydroxycoumarin, 2-aminooctanoate (alpha-aminocaprylic acid), 10-undecenoate (11:1n1) (undecylenic acid), 1-linoleoyl-GPA (18:2) (lysophosphatidic acid; LPA 18:2) are observed. These metabolites are either directly food derived or are products of host and gut microbial metabolism of food-derived products. Our Mendelian randomization analysis suggests that low hippurate levels may be in the causal pathway leading towards depression. Our findings highlight putative actionable targets for depression prevention that are easily modifiable through diet interventions.

Association of mental health and negative life events with weight change in patients with overweight: A cohort study.

BACKGROUND: It is unclear to what extent mental health and negative life events (NLEs) contribute to weight change in patients with overweight. This study aimed to evaluate the association of anxiety, depression, NLEs and quality of life (QoL) with weight change over ten years in middle-aged individuals with overweight. METHODS: Population-based cohort study of 2889 middle-aged men and women with a body mass index ≥27 kg/m2. Relative weight change over ten years was defined as weight loss (≤- 5 %), stable weight (between >- 5 % and <5 %) or weight gain (≥5 %). At baseline, participants reported anxiety symptoms, depressive symptoms, recent (last year) and distant (lifetime) NLEs, and a mental component summary of QoL. With multinomial logistic regression adjusting for potential confounding, we examined the association of mental health and NLEs with weight change after a median (25th, 75th percentiles) follow-up of 9.7 (9.0-10.5) years. RESULTS: In 51 % participants weight was stable, 33 % participants lost weight and 17 % gained weight. Mild (odds ratio 1.36; 95 % confidence interval 1.05-1.75), and moderate to very severe depressive symptoms (1.43; 0.97-2.12) and four or more distant NLEs (1.35; 1.10-1.67) were associated with weight gain. Anxiety symptoms, the mental component summary of QoL were not associated with either weight gain or weight loss. LIMITATIONS: Due to the observational design residual confounding cannot be excluded. CONCLUSION: Our study suggests that depressive symptoms or having experienced distant NLEs are associated with weight gain over time in middle-aged individuals with overweight. These subgroups might benefit from proactive attention from their health care providers.

Hepatic triglyceride content is intricately associated with numerous metabolites and biochemical pathways.

BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is characterized by the pathological accumulation of triglycerides in hepatocytes and is associated with insulin resistance, atherogenic dyslipidaemia and cardiometabolic diseases. Thus far, the extent of metabolic dysregulation associated with hepatic triglyceride accumulation has not been fully addressed. In this study, we aimed to identify metabolites associated with hepatic triglyceride content (HTGC) and map these associations using network analysis. METHODS: To gain insight in the spectrum of metabolites associated with hepatic triglyceride accumulation, we performed a comprehensive plasma metabolomics screening of 1363 metabolites in apparently healthy middle aged (age 45-65) individuals (N = 496) in whom HTGC was measured by proton magnetic resonance spectroscopy. An atlas of metabolite-HTGC associations, based on univariate results, was created using correlation-based Gaussian graphical model (GGM) and genome scale metabolic model network analyses. Pathways associated with the clinical prognosis marker fibrosis 4 (FIB-4) index were tested using a closed global test. RESULTS: Our analyses revealed that 118 metabolites were univariately associated with HTGC (p-value <6.59 × 10-5 ), including 106 endogenous, 1 xenobiotic and 11 partially characterized/uncharacterized metabolites. These associations were mapped to several biological pathways including branched amino acids (BCAA), diglycerols, sphingomyelin, glucosyl-ceramide and lactosyl-ceramide. We also identified a novel possible HTGC-related pathway connecting glutamate, metabolonic lactone sulphate and X-15245 using the GGM network. These pathways were confirmed to be associated with the FIB-4 index as well. The full interactive metabolite-HTGC atlas is provided online: https://tofaquih.github.io/AtlasLiver/. CONCLUSIONS: The combined network and pathway analyses indicated extensive associations between BCAA and the lipids pathways with HTGC and the FIB-4 index. Moreover, we report a novel pathway glutamate-metabolonic lactone sulphate-X-15245 with a potential strong association with HTGC. These findings can aid elucidating HTGC metabolomic profiles and provide insight into novel drug targets for fibrosis-related outcomes.

Normal range CAG repeat size variations in the HTT gene are associated with an adverse lipoprotein profile partially mediated by body mass index.

Tandem cytosine-adenine-guanine (CAG) repeat sizes of 36 or more in the huntingtin gene (HTT) cause Huntington's disease (HD). Apart from neuropsychiatric complications, the disease is also accompanied by metabolic dysregulation and weight loss, which contribute to a progressive functional decline. Recent studies also reported an association between repeats below the pathogenic threshold (<36) for HD and body mass index (BMI), suggesting that HTT repeat sizes in the non-pathogenic range are associated with metabolic dysregulation. In this study, we hypothesized that HTT repeat sizes < 36 are associated with metabolite levels, possibly mediated through reduced BMI. We pooled data from three European cohorts (n = 10 228) with genotyped HTT CAG repeat size and metabolomic measurements. All 145 metabolites were measured on the same targeted platform in all studies. Multilevel mixed-effects analysis using the CAG repeat size in HTT identified 67 repeat size metabolite associations. Overall, the metabolomic profile associated with larger CAG repeat sizes in HTT were unfavorable-similar to those of higher risk of coronary artery disease and type 2 diabetes-and included elevated levels of amino acids, fatty acids, low-density lipoprotein (LDL)-, very low-density lipoprotein- and intermediate density lipoprotein (IDL)-related metabolites while with decreased levels of very large high-density lipoprotein (HDL)-related metabolites. Furthermore, the associations of 50 metabolites, in particular, specific very large HDL-related metabolites, were mediated by lower BMI. However, no mediation effect was found for 17 metabolites related to LDL and IDL. In conclusion, our findings indicate that large non-pathogenic CAG repeat sizes in HTT are associated with an unfavorable metabolomic profile despite their association with a lower BMI.

The association between adiposity and atypical energy-related symptoms of depression: A role for metabolic dysregulations.

BACKGROUND: Adiposity has been shown to be linked with atypical energy-related symptoms (AES) of depression. We used genomics to separate the effect of adiposity from that of metabolic dysregulations to examine whether the link between obesity and AES is dependent on the presence of metabolic dysregulations. METHOD: Data were from NEO (n = 5734 individuals) and NESDA (n = 2238 individuals) cohorts, in which the Inventory of Depressive Symptomatology (IDS-SR30) was assessed. AES profile was based on four symptoms: increased appetite, increased weight, low energy level, and leaden paralysis. We estimated associations between AES and two genetic risk scores (GRS) indexing increasing total body fat with (metabolically unhealthy adiposity, GRS-MUA) and without (metabolically healthy adiposity, GRS-MHA) metabolic dysregulations. RESULTS: We validated that both GRS-MUA and GRS-MHA were associated with higher total body fat in NEO study, but divergently associated with biomarkers of metabolic health (e.g., fasting glucose and HDL-cholesterol) in both cohorts. In the pooled results, per standard deviation, GRS-MUA was specifically associated with a higher AES score (ß = 0.03, 95%CI: 0.01; 0.05), while there was no association between GRS-MHA and AES (ß = -0.01, 95%CI: -0.03; 0.01). CONCLUSION: These results suggest that the established link between adiposity and AES profile emerges in the presence of metabolic dysregulations, which may represent the connecting substrate between the two conditions.

Metabolomics dissection of depression heterogeneity and related cardiometabolic risk.

BACKGROUND: A recent hypothesis postulates the existence of an 'immune-metabolic depression' (IMD) dimension characterized by metabolic dysregulations. Combining data on metabolomics and depressive symptoms, we aimed to identify depressions associated with an increased risk of adverse metabolic alterations. METHOD: Clustering data were from 1094 individuals with major depressive disorder in the last 6 months and measures of 149 metabolites from a 1H-NMR platform and 30 depressive symptoms (IDS-SR30). Canonical correlation analyses (CCA) were used to identify main independent metabolite-symptom axes of variance. Then, for the replication, we examined the association of the identified dimensions with metabolites from the same platform and cardiometabolic diseases in an independent population-based cohort (n = 6572). RESULTS: CCA identified an overall depression dimension and a dimension resembling IMD, in which symptoms such as sleeping too much, increased appetite, and low energy level had higher relative loading. In the independent sample, the overall depression dimension was associated with lower cardiometabolic risk, such as (i.e. per s.d.) HOMA-1B -0.06 (95% CI -0.09 - -0.04), and visceral adipose tissue -0.10 cm2 (95% CI -0.14 - -0.07). In contrast, the IMD dimension was associated with well-known cardiometabolic diseases such as higher visceral adipose tissue 0.08 cm2 (95% CI 0.04-0.12), HOMA-1B 0.06 (95% CI 0.04-0.09), and lower HDL-cholesterol levels -0.03 mmol/L (95% CI -0.05 - -0.01). CONCLUSIONS: Combining metabolomics and clinical symptoms we identified a replicable depression dimension associated with adverse metabolic alterations, in line with the IMD hypothesis. Patients with IMD may be at higher cardiometabolic risk and may benefit from specific treatment targeting underlying metabolic dysregulations.

Agreement between nicotine metabolites in blood and self-reported smoking status: The Netherlands Epidemiology of Obesity study.

Introduction: Self-report and nicotine detection are methods to measure smoking exposure and can both lead to misclassification. It is important to highlight discrepancies between these two methods in the context of epidemiological research. Objective: The aim of this cross-sectional study is to assess the agreements between self-reported smoking status and nicotine metabolite detection. Methods: Data of 599 participants from the Netherlands Epidemiology of Obesity study were used to compare serum metabolite levels of five nicotine metabolites (cotinine, hydroxy-cotinine, cotinine N-Oxide, norcotinine, 3-hydroxy-cotinine-glucuronide) between self-reported never smokers (n = 245), former smokers (n = 283) and current smokers (n = 71). We assessed whether metabolites were absent or present and used logistic regression to discriminate between current and never smokers based on nicotine metabolite information. A classification tree was derived to classify individuals into current smokers and non/former smokers based on metabolite information. Results: In 94% of the self-reported current smokers, at least one metabolite was present, versus in 19% of the former smokers and in 10% of the never smokers. In none of the never smokers, cotinine-n-oxide, 3-hydroxy-cotinine-n-glucorinide or norcotinine was present, while at least one of these metabolites was detected in 68% of the self-reported current smokers. The classification tree classified 95% of the participants in accordance to their self-reported smoking status. All self-reported smokers who were classified as non-smokers according to the metabolite profile, had reported to be occasional smokers. Conclusion: The agreement between self-reported smoking status and metabolite information was high. This indicates that self-reported smoking status is generally reliable.

The Roles of Gut Microbiome and Plasma Metabolites in the Associations between ABO Blood Groups and Insulin Homeostasis: The Microbiome and Insulin Longitudinal Evaluation Study (MILES).

Non-O blood groups are associated with decreased insulin sensitivity and risk of type 2 diabetes. A recent study pinpointed the associations between ABO blood groups and gut microbiome, which may serve as potential mediators for the observed increased disease risks. We aimed to characterize associations between ABO haplotypes and insulin-related traits as well as potential mediating pathways. We assessed insulin homeostasis in African Americans (AAs; n = 109) and non-Hispanic whites (n = 210) from the Microbiome and Insulin Longitudinal Evaluation Study. The ABO haplotype was determined by six SNPs located in the ABO gene. Based on prior knowledge, we included 21 gut bacteria and 13 plasma metabolites for mediation analysis. In the white study cohort (60 ± 9 years, 42% male), compared to the O1 haplotype, A1 was associated with a higher Matsuda insulin sensitivity index, while a lower relative abundance of Bacteroides massiliensis and lactate levels. Lactate was a likely mediator of this association but not Bacteroides massiliensis. In the AAs group (57 ± 8 years, 33% male), we found no association between any haplotype and insulin-related traits. In conclusion, the A1 haplotype may promote healthy insulin sensitivity in non-Hispanic whites and lactate likely play a role in this process but not selected gut bacteria.

[Code dark grey in hospitals: short hospital admission and high mortality due to COVID-19]. / Code donkergrijs in het ziekenhuis.

During the COVID-19 pandemic, we have experienced several waves in which the number of hospital beds occupied by patients with COVID-19 has varied greatly. In December 2022, hospitals were under a tremendous pressure, and were forced to upgrade their capacity to phase 2D ("Code Dark Grey"). This is the last phase prior to phase 3 ("Code Black"), in which we would be unable to treat all patients and would be forced to triage based on medical and non-medical characteristics of the patients. In this brief analysis, we demonstrate that phase 2D is characterized by a relatively short mean period of hospital admission and a higher hospital mortality.

Evaluation of the Value of Waist Circumference and Metabolomics in the Estimation of Visceral Adipose Tissue.

Visceral adipose tissue (VAT) is a strong prognostic factor for cardiovascular disease and a potential target for cardiovascular risk stratification. Because VAT is difficult to measure in clinical practice, we estimated prediction models with predictors routinely measured in general practice and VAT as outcome using ridge regression in 2,501 middle-aged participants from the Netherlands Epidemiology of Obesity study, 2008-2012. Adding waist circumference and other anthropometric measurements on top of the routinely measured variables improved the optimism-adjusted R2 from 0.50 to 0.58 with a decrease in the root-mean-square error (RMSE) from 45.6 to 41.5 cm2 and with overall good calibration. Further addition of predominantly lipoprotein-related metabolites from the Nightingale platform did not improve the optimism-corrected R2 and RMSE. The models were externally validated in 370 participants from the Prospective Investigation of Vasculature in Uppsala Seniors (PIVUS, 2006-2009) and 1,901 participants from the Multi-Ethnic Study of Atherosclerosis (MESA, 2000-2007). Performance was comparable to the development setting in PIVUS (R2 = 0.63, RMSE = 42.4 cm2, calibration slope = 0.94) but lower in MESA (R2 = 0.44, RMSE = 60.7 cm2, calibration slope = 0.75). Our findings indicate that the estimation of VAT with routine clinical measurements can be substantially improved by incorporating waist circumference but not by metabolite measurements.

Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts.

OBJECTIVE: Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed ß-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed. RESEARCH DESIGN AND METHODS: Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD). RESULTS: Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway. CONCLUSIONS: Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.

Associations of metabolomic profiles with circulating vitamin E and urinary vitamin E metabolites in middle-aged individuals.

Vitamin E (α-tocopherol [α-TOH]) is transported in lipoprotein particles in blood, but little is known about the transportation of its oxidized metabolites. In the Netherlands Epidemiology of Obesity Study, we aimed to investigate the associations of 147 circulating metabolomic measures obtained through targeted nuclear magnetic resonance with serum α-TOH and its urinary enzymatic (α-CEHC) and oxidized (α-TLHQ) metabolites from 24-h urine quantified by liquid chromatography with tandem mass spectrometry. Multivariable linear regression analyses, in which multiple testing was taken into account, were performed to assess associations between metabolomic measures (determinants; standardized to mean = 0, SD = 1) and vitamin E metabolites (outcomes), adjusted for demographic factors. We analyzed 474 individuals (55% women, 45% men) with a mean (SD) age of 55.7 (6.0) y. Out of 147 metabolomic measures, 106 were associated (P < 1.34 × 10-3) with serum α-TOH (median ß [interquartile range] = 0.416 [0.383-0.466]), predominantly lipoproteins associated with higher α-TOH. The associations of metabolomic measures with urinary α-CEHC have directions similar to those with α-TOH, but effect sizes were smaller and non-significant (median ß [interquartile range] = 0.065 [0.047-0.084]). However, associations of metabolomic measures with urinary α-TLHQ were markedly different from those with both serum α-TOH and urinary α-CEHC, with negative and small-to-null relations to most very-low-density lipoproteins and amino acids. Therefore, our results highlight the differences in the lipoproteins involved in the transportation of circulating α-TOH and oxidized vitamin E metabolites. This indicates that circulating α-TOH may be representative of the enzymatic but not the antioxidative function of vitamin E.

Higher thyrotropin leads to unfavorable lipid profile and somewhat higher cardiovascular disease risk: evidence from multi-cohort Mendelian randomization and metabolomic profiling.

BACKGROUND: Observational studies suggest interconnections between thyroid status, metabolism, and risk of coronary artery disease (CAD), but causality remains to be proven. The present study aimed to investigate the potential causal relationship between thyroid status and cardiovascular disease and to characterize the metabolomic profile associated with thyroid status. METHODS: Multi-cohort two-sample Mendelian randomization (MR) was performed utilizing genome-wide significant variants as instruments for standardized thyrotropin (TSH) and free thyroxine (fT4) within the reference range. Associations between TSH and fT4 and metabolic profile were investigated in a two-stage manner: associations between TSH and fT4 and the full panel of 161 metabolomic markers were first assessed hypothesis-free, then directional consistency was assessed through Mendelian randomization, another metabolic profile platform, and in individuals with biochemically defined thyroid dysfunction. RESULTS: Circulating TSH was associated with 52/161 metabolomic markers, and fT4 levels were associated with 21/161 metabolomic markers among 9432 euthyroid individuals (median age varied from 23.0 to 75.4 years, 54.5% women). Positive associations between circulating TSH levels and concentrations of very low-density lipoprotein subclasses and components, triglycerides, and triglyceride content of lipoproteins were directionally consistent across the multivariable regression, MR, metabolomic platforms, and for individuals with hypo- and hyperthyroidism. Associations with fT4 levels inversely reflected those observed with TSH. Among 91,810 CAD cases and 656,091 controls of European ancestry, per 1-SD increase of genetically determined TSH concentration risk of CAD increased slightly, but not significantly, with an OR of 1.03 (95% CI 0.99-1.07; p value 0.16), whereas higher genetically determined fT4 levels were not associated with CAD risk (OR 1.00 per SD increase of fT4; 95% CI 0.96-1.04; p value 0.59). CONCLUSIONS: Lower thyroid status leads to an unfavorable lipid profile and a somewhat increased cardiovascular disease risk.

Genetic Studies of Metabolomics Change After a Liquid Meal Illuminate Novel Pathways for Glucose and Lipid Metabolism.

Humans spend the greater part of the day in a postprandial state. However, the genetic basis of postprandial blood measures is relatively uncharted territory. We examined the genetics of variation in concentrations of postprandial metabolites (t = 150 min) in response to a liquid mixed meal through genome-wide association studies (GWAS) performed in the Netherlands Epidemiology of Obesity (NEO) study (n = 5,705). The metabolite response GWAS identified an association between glucose change and rs10830963:G in the melatonin receptor 1B (ß [SE] -0.23 [0.03], P = 2.15 × 10-19). In addition, the ANKRD55 locus led by rs458741:C showed strong associations with extremely large VLDL (XXLVLDL) particle response (XXLVLDL total cholesterol: ß [SE] 0.17 [0.03], P = 5.76 × 10-10; XXLVLDL cholesterol ester: ß [SE] 0.17 [0.03], P = 9.74 × 10-10), which also revealed strong associations with body composition and diabetes in the UK Biobank (P < 5 × 10-8). Furthermore, the associations between XXLVLDL response and insulinogenic index, HOMA-ß, Matsuda insulin sensitivity index, and HbA1c in the NEO study implied the role of chylomicron synthesis in diabetes (with false discovery rate-corrected q <0.05). To conclude, genetic studies of metabolomics change after a liquid meal illuminate novel pathways for glucose and lipid metabolism. Further studies are warranted to corroborate biological pathways of the ANKRD55 locus underlying diabetes.

Rare and low-frequency exonic variants and gene-by-smoking interactions in pulmonary function.

Genome-wide association studies have identified numerous common genetic variants associated with spirometric measures of pulmonary function, including forced expiratory volume in one second (FEV1), forced vital capacity, and their ratio. However, variants with lower minor allele frequencies are less explored. We conducted a large-scale gene-smoking interaction meta-analysis on exonic rare and low-frequency variants involving 44,429 individuals of European ancestry in the discovery stage and sought replication in the UK BiLEVE study with 45,133 European ancestry samples and UK Biobank study with 59,478 samples. We leveraged data on cigarette smoking, the major environmental risk factor for reduced lung function, by testing gene-by-smoking interaction effects only and simultaneously testing the genetic main effects and interaction effects. The most statistically significant signal that replicated was a previously reported low-frequency signal in GPR126, distinct from common variant associations in this gene. Although only nominal replication was obtained for a top rare variant signal rs142935352 in one of the two studies, interaction and joint tests for current smoking and PDE3B were significantly associated with FEV1. This study investigates the utility of assessing gene-by-smoking interactions and underscores their effects on potential pulmonary function.