Metabolome-wide association study on ABCA7 indicates a role of ceramide metabolism in Alzheimer's disease.

Genome-wide association studies (GWASs) have identified genetic loci associated with the risk of Alzheimer's disease (AD), but the molecular mechanisms by which they confer risk are largely unknown. We conducted a metabolome-wide association study (MWAS) of AD-associated loci from GWASs using untargeted metabolic profiling (metabolomics) by ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). We identified an association of lactosylceramides (LacCer) with AD-related single-nucleotide polymorphisms (SNPs) in ABCA7 (P = 5.0 × 10-5 to 1.3 × 10-44). We showed that plasma LacCer concentrations are associated with cognitive performance and genetically modified levels of LacCer are associated with AD risk. We then showed that concentrations of sphingomyelins, ceramides, and hexosylceramides were altered in brain tissue from Abca7 knockout mice, compared with wild type (WT) (P = 0.049-1.4 × 10-5), but not in a mouse model of amyloidosis. Furthermore, activation of microglia increases intracellular concentrations of hexosylceramides in part through induction in the expression of sphingosine kinase, an enzyme with a high control coefficient for sphingolipid and ceramide synthesis. Our work suggests that the risk for AD arising from functional variations in ABCA7 is mediated at least in part through ceramides. Modulation of their metabolism or downstream signaling may offer new therapeutic opportunities for AD.

Genetic investigation into the broad health implications of caffeine: evidence from phenome-wide, proteome-wide and metabolome-wide Mendelian randomization.

BACKGROUND: Caffeine is one of the most utilized drugs in the world, yet its clinical effects are not fully understood. Circulating caffeine levels are influenced by the interplay between consumption behaviour and metabolism. This study aimed to investigate the effects of circulating caffeine levels by considering genetically predicted variation in caffeine metabolism. METHODS: Leveraging genetic variants related to caffeine metabolism that affect its circulating levels, we investigated the clinical effects of plasma caffeine in a phenome-wide association study (PheWAS). We validated novel findings using a two-sample Mendelian randomization framework and explored the potential mechanisms underlying these effects in proteome-wide and metabolome-wide Mendelian randomization. RESULTS: Higher levels of genetically predicted circulating caffeine among caffeine consumers were associated with a lower risk of obesity (odds ratio (OR) per standard deviation increase in caffeine = 0.97, 95% confidence interval (CI) CI: 0.95-0.98, p = 2.47 × 10-4), osteoarthrosis (OR = 0.97, 95% CI: 0.96-0.98, P=1.10 × 10-8) and osteoarthritis (OR: 0.97, 95% CI: 0.96 to 0.98, P = 1.09 × 10-6). Approximately one third of the protective effect of plasma caffeine on osteoarthritis risk was estimated to be mediated through lower bodyweight. Proteomic and metabolomic perturbations indicated lower chronic inflammation, improved lipid profiles, and altered protein and glycogen metabolism as potential biological mechanisms underlying these effects. CONCLUSIONS: We report novel evidence suggesting that long-term increases in circulating caffeine may reduce bodyweight and the risk of osteoarthrosis and osteoarthritis. We confirm prior genetic evidence of a protective effect of plasma caffeine on risk of overweight and obesity. Further clinical study is warranted to understand the translational relevance of these findings before clinical practice or lifestyle interventions related to caffeine consumption are introduced.

Multiple long-term conditions in people with psoriasis: a latent class and bidirectional Mendelian randomization analysis.

BACKGROUND: Coexisting long-term conditions (LTCs) in psoriasis and their potential causal associations with the disease are not well -established. OBJECTIVES: To determine distinct clusters of LTCs in people with psoriasis and the potential bidirectional causal association between these LTCs and psoriasis. METHODS: Using latent class analysis, cross-sectional data from people with psoriasis from the UK Biobank were analysed to identify distinct psoriasis-related comorbidity profiles. Linkage disequilibrium score regression (LDSR) was applied to compute the genetic correlation between psoriasis and LTCs. Two-sample bidirectional Mendelian randomization (MR) analysis assessed the potential causal direction using independent genetic variants that reached genome-wide significance (P < 5 × 10-8). RESULTS: Five comorbidity clusters were identified in a population of 10 873 people with psoriasis. LDSR revealed that psoriasis was positively genetically correlated with heart failure [genetic correlation (rg) = 0.23, P = 8.8 × 10-8], depression (rg = 0.12, P = 2.7 × 10-5), coronary artery disease (CAD; rg = 0.15, P = 2 × 10-4) and type 2 diabetes (rg = 0.19, P = 3 × 10-3). Genetic liability to CAD was associated with an increased risk of psoriasis [inverse variance weighted (IVW) odds ratio (ORIVW) 1.159, 95% confidence interval (CI) 1.055-1.274; P = 2 × 10-3]. The MR pleiotropy residual sum and outlier (MR-PRESSO; ORMR-PRESSO 1.13, 95% CI 1.042-1.228; P = 6 × 10-3) and the MR-robust adjusted profile score (RAPS) (ORMR-RAPS 1.149, 95% CI 1.062-1.242; P = 5 × 10-4) approaches corroborate the IVW findings. The weighted median (WM) generated similar and consistent effect estimates but was not statistically significant (ORWM 1.076, 95% CI 0.949-1.221; P = 0.25). Evidence for a suggestive increased risk was detected for CAD (ORIVW 1.031, 95% CI 1.003-1.059; P = 0.03) and heart failure (ORIVW 1.019, 95% CI 1.005-1.033; P = 9 × 10-3) in those with a genetic liability to psoriasis; however, MR sensitivity analyses did not reach statistical significance. CONCLUSIONS: Five distinct clusters of psoriasis comorbidities were observed with these findings to offer opportunities for an integrated approach to comorbidity prevention and treatment. Coexisting LTCs share with psoriasis common genetic and nongenetic risk factors, and aggressive lifestyle modification in these people is anticipated to have an impact beyond psoriasis risk. Genetically predicted CAD is possibly associated with an increased risk of psoriasis, altering our prior knowledge.

Metabolomic Profiling of Cholesterol Efflux Capacity in a Multiethnic Population: Insights From MESA.

BACKGROUND: Impaired cholesterol efflux capacity (CEC) is a novel lipid metabolism trait associated with atherosclerotic cardiovascular disease. Mechanisms underlying CEC variation are unknown. We evaluated associations of circulating metabolites with CEC to advance understanding of metabolic pathways involved in cholesterol efflux regulation. METHODS: Participants enrolled in the MESA (Multi-Ethnic Study of Atherosclerosis) who underwent nuclear magnetic resonance metabolome profiling and CEC measurement (N=3543) at baseline were included. Metabolite associations with CEC were evaluated using standard linear regression analyses. Repeated ElasticNet and multilayer perceptron regression were used to assess metabolite profile predictive performance for CEC. Features important for CEC prediction were identified using Shapley Additive Explanations values. RESULTS: Greater CEC was significantly associated with metabolite clusters composed of the largest-sized particle subclasses of VLDL (very-low-density lipoprotein) and HDL (high-density lipoprotein), as well as their constituent apo A1, apo A2, phospholipid, and cholesterol components (ß=0.072-0.081; P<0.001). Metabolite profiles had poor accuracy for predicting in vitro CEC in linear and nonlinear analyses (R2<0.02; Spearman ρ<0.18). The most important feature for CEC prediction was race, with Black participants having significantly lower CEC compared with other races. CONCLUSIONS: We identified independent associations among CEC, the largest-sized particle subclasses of VLDL and HDL, and their constituent apolipoproteins and lipids. A large proportion of variation in CEC remained unexplained by metabolites and traditional clinical risk factors, supporting further investigation into genomic, proteomic, and phospholipidomic determinants of CEC.

Genetic Architecture of Acute Myocarditis and the Overlap With Inherited Cardiomyopathy.

BACKGROUND: Acute myocarditis is an inflammatory condition that may herald the onset of dilated cardiomyopathy (DCM) or arrhythmogenic cardiomyopathy (ACM). We investigated the frequency and clinical consequences of DCM and ACM genetic variants in a population-based cohort of patients with acute myocarditis. METHODS: This was a population-based cohort of 336 consecutive patients with acute myocarditis enrolled in London and Maastricht. All participants underwent targeted DNA sequencing for well-characterized cardiomyopathy-associated genes with comparison to healthy controls (n=1053) sequenced on the same platform. Case ascertainment in England was assessed against national hospital admission data. The primary outcome was all-cause mortality. RESULTS: Variants that would be considered pathogenic if found in a patient with DCM or ACM were identified in 8% of myocarditis cases compared with <1% of healthy controls (P=0.0097). In the London cohort (n=230; median age, 33 years; 84% men), patients were representative of national myocarditis admissions (median age, 32 years; 71% men; 66% case ascertainment), and there was enrichment of rare truncating variants (tv) in ACM-associated genes (3.1% of cases versus 0.4% of controls; odds ratio, 8.2; P=0.001). This was driven predominantly by DSP-tv in patients with normal LV ejection fraction and ventricular arrhythmia. In Maastricht (n=106; median age, 54 years; 61% men), there was enrichment of rare truncating variants in DCM-associated genes, particularly TTN-tv, found in 7% (all with left ventricular ejection fraction <50%) compared with 1% in controls (odds ratio, 3.6; P=0.0116). Across both cohorts over a median of 5.0 years (interquartile range, 3.9-7.8 years), all-cause mortality was 5.4%. Two-thirds of deaths were cardiovascular, attributable to worsening heart failure (92%) or sudden cardiac death (8%). The 5-year mortality risk was 3.3% in genotype-negative patients versus 11.1% for genotype-positive patients (Padjusted=0.08). CONCLUSIONS: We identified DCM- or ACM-associated genetic variants in 8% of patients with acute myocarditis. This was dominated by the identification of DSP-tv in those with normal left ventricular ejection fraction and TTN-tv in those with reduced left ventricular ejection fraction. Despite differences between cohorts, these variants have clinical implications for treatment, risk stratification, and family screening. Genetic counseling and testing should be considered in patients with acute myocarditis to help reassure the majority while improving the management of those with an underlying genetic variant.

Pathway-based integration of multi-omics data reveals lipidomics alterations validated in an Alzheimer's disease mouse model and risk loci carriers.

Alzheimer's disease (AD) is a highly prevalent neurodegenerative disorder. Despite increasing evidence of the importance of metabolic dysregulation in AD, the underlying metabolic changes that may impact amyloid plaque formation are not understood, particularly for late-onset AD. This study analyzed genome-wide association studies (GWAS), transcriptomics, and proteomics data obtained from several data repositories to obtain differentially expressed (DE) multi-omics elements in mouse models of AD. We characterized the metabolic modulation in these data sets using gene ontology, transcription factor, pathway, and cell-type enrichment analyses. A predicted lipid signature was extracted from genome-scale metabolic networks (GSMN) and subsequently validated in a lipidomic data set derived from cortical tissue of ABCA-7 null mice, a mouse model of one of the genes associated with late-onset AD. Moreover, a metabolome-wide association study (MWAS) was performed to further characterize the association between dysregulated lipid metabolism in human blood serum and genes associated with AD risk. We found 203 DE transcripts, 164 DE proteins, and 58 DE GWAS-derived mouse orthologs associated with significantly enriched metabolic biological processes. Lipid and bioenergetic metabolic pathways were significantly over-represented across the AD multi-omics data sets. Microglia and astrocytes were significantly enriched in the lipid-predominant AD-metabolic transcriptome. We also extracted a predicted lipid signature that was validated and robustly modeled class separation in the ABCA7 mice cortical lipidome, with 11 of these lipid species exhibiting statistically significant modulations. MWAS revealed 298 AD single nucleotide polymorphisms-metabolite associations, of which 70% corresponded to lipid classes. These results support the importance of lipid metabolism dysregulation in AD and highlight the suitability of mapping AD multi-omics data into GSMNs to identify metabolic alterations.

Metabolomic Profile of the Healthy Eating Index-2015 in the Multiethnic Study of Atherosclerosis.

BACKGROUND: Poor diet quality is a risk factor for type 2 diabetes and cardiovascular disease. However, knowledge of metabolites marking adherence to Dietary Guidelines for Americans (2015 version) are limited. OBJECTIVES: The goal was to determine a pattern of metabolites associated with the Healthy Eating Index (HEI)-2015, which measures adherence to the Dietary Guidelines for Americans. METHODS: The analysis examined 3557 adult men and women from the longitudinal cohort Multiethnic Study of Atherosclerosis (MESA), without known cardiovascular disease and with complete dietary data. Fasting serum specimens and diet and demographic questionnaires were assessed at baseline. Untargeted 1H 1-dimensional nuclei magnetic resonance spectroscopy (600 MHz) was used to generate metabolomics and lipidomics. A metabolome-wide association study specified each spectral feature as outcomes, HEI-2015 score as predictor, adjusting for age, sex, race, and study site in linear regression analyses. Subsequently, hierarchical clustering defined the discrete groups of correlated nuclei magnetic resonance features associated with named metabolites, and the linear regression analysis assessed for associations with HEI-2015 total and component scores. RESULTS: The sample included 50% women with an mean age of 63 years, with 40% identifying as White, 23% as Black, 24% as Hispanic, and 13% as Chinese American. The mean HEI-2015 score was 66. The metabolome-wide association study identified 179 spectral features significantly associated with HEI-2015 score. The cluster analysis identified 7 clusters representing 4 metabolites; HEI-2015 score was significantly associated with all. HEI-2015 score was associated with proline betaine [ß = 0.12 (SE = 0.02); P = 4.70 × 10-13] and was inversely related to proline [ß = -0.13 (SE = 0.02); P = 4.45 × 10-14], 1,5 anhydrosorbitol [ß = -0.08 (SE = 0.02); P = 4.37 × 10-7] and unsaturated fatty acyl chains [ß = 0.08 (SE = 0.02); P = 8.98 × 10-7]. Intake of total fruit, whole grains, and seafood and plant proteins was associated with proline betaine. CONCLUSIONS: Diet quality is significantly associated with unsaturated fatty acyl chains, proline betaine, and proline. Further analysis may clarify the link between diet quality, metabolites, and pathogenesis of cardiometabolic disease.

Associations between Metabolomic Biomarkers of Avocado Intake and Glycemia in the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Avocado consumption is linked to better glucose homeostasis, but small associations suggest potential population heterogeneity. Metabolomic data capture the effects of food intake after digestion and metabolism, thus accounting for individual differences in these processes. OBJECTIVES: To identify metabolomic biomarkers of avocado intake and to examine their associations with glycemia. METHODS: Baseline data from 6224 multi-ethnic older adults (62% female) included self-reported avocado intake, fasting glucose and insulin, and untargeted plasma proton nuclear magnetic resonance metabolomic features (metabolomic data were available for a randomly selected subset; N = 3438). Subsequently, incident type 2 diabetes (T2D) was assessed over an ∼18 y follow-up period. A metabolome-wide association study of avocado consumption status (consumer compared with nonconsumer) was conducted, and the relationship of these features with glycemia via cross-sectional associations with fasting insulin and glucose and longitudinal associations with incident T2D was examined. RESULTS: Three highly-correlated spectral features were associated with avocado intake at metabolome-wide significance levels (P < 5.3 ∗ 10-7) and combined into a single biomarker. We did not find evidence that these features were additionally associated with overall dietary quality, nor with any of 47 other food groups (all P > 0.001), supporting their suitability as a biomarker of avocado intake. Avocado intake showed a modest association only with lower fasting insulin (ß = -0.07 +/- 0.03, P = 0.03), an association that was attenuated to nonsignificance when additionally controlling for body mass index (kg/m2). However, our biomarker of avocado intake was strongly associated with lower fasting glucose (ß = -0.22 +/- 0.02, P < 2.0 ∗ 10-16), lower fasting insulin (ß = -0.17 +/- 0.02, P < 2.0 ∗ 10-16), and a lower incidence of T2D (hazard ratio: 0.68; 0.63-074, P < 2.0 ∗ 10-16), even when adjusting for BMI. CONCLUSIONS: Highly significant associations between glycemia and avocado-related metabolomic features, which serve as biomarkers of the physiological impact of dietary intake after digestion and absorption, compared to modest relationships between glycemia and avocado consumption, highlights the importance of considering individual differences in metabolism when considering diet-health relationships.

Investigating modifiable pathways in psoriasis: A Mendelian randomization study.

BACKGROUND: Potentially modifiable risk factors have previously been investigated only in conventional observational studies. OBJECTIVE: To assess whether genetically predicted exposures to modifiable factors are associated with the risk of psoriasis. METHODS: Two-sample Mendelian randomization (MR) analysis. RESULTS: An increased risk of psoriasis was noted for genetically predicted lifetime smoking index (odds ratio [OR]MR-IVW = 2.11; 95% confidence interval [CI], 1.28-3.51), childhood (OR MR-IVW = 1.40; 95% CI, 1.14-1.71) and adult body mass index (OR MR-IVW = 1.63; 95% CI, 1.32-2), waist (OR IVW = 1.86; 95% CI, 1.31-2.64), and hip circumference (OR MR-IVW = 1.55; 95% CI, 1.15-2.07). Protective association was also reported between genetically predicted longer sleep duration (OR MR-IVW = 0.56; 95% CI 0.37-0.84) and increased years of education (OR MR-IVW = 0.78; 95% CI, 0.62-0.98). This effect of education persisted in multivariable MR after adjusting for genetic predictors of smoking and adult body mass index (ORMVMR-IVW = 0.72; 95% CI, 0.56-0.92). LIMITATIONS: It was not possible to stratify for psoriasis severity. CONCLUSION: Smoking cessation and prevention of obesity are important strategies for decreasing the incidence of psoriasis. Similarly, targeting education inequality is expected to lead further to reductions in cases of psoriasis.

Dementia risk in patients with type 2 diabetes: Comparing metformin with no pharmacological treatment.

INTRODUCTION: Metformin has been suggested as a therapeutic agent for dementia, but the relevant evidence has been partial and inconsistent. METHODS: We established a national cohort of 210,237 type 2 diabetes patients in the UK Clinical Practice Research Datalink. Risks of incident dementia were compared between metformin initiators and those who were not prescribed any anti-diabetes medication during follow-up. RESULTS: Compared with metformin initiators (n = 114,628), patients who received no anti-diabetes medication (n = 95,609) had lower HbA1c and better cardiovascular health at baseline. Both Cox regression and propensity score weighting analysis showed metformin initiators had lower risk of dementia compared to those non-users (adjusted hazard ratio = 0.88 [95% confidence interval: 0.84-0.92] and 0.90 [0.84-0.96]). Patients on long-term metformin treatment had an even lower risk of dementia. DISCUSSION: Metformin may act beyond its glycemic effect and reduce dementia risk to an even lower level than that of patients with milder diabetes and better health profiles. HIGHLIGHTS: Metformin initiators had a significantly lower risk of dementia compared with patients not receiving anti-diabetes medication. Compared with metformin initiators, diabetes patients not receiving pharmacological treatment had better glycemic profiles at baseline and during follow-up. Patients on long-term metformin treatment had an even lower risk of subsequent dementia incidence. Metformin may act beyond its effect on hyperglycemia and has the potential of being repurposed for dementia prevention.

Diet-wide association study of 92 foods and nutrients and lung cancer risk in the European Prospective Investigation into Cancer and Nutrition study and the Netherlands Cohort Study.

It is unclear whether diet, and in particular certain foods or nutrients, are associated with lung cancer risk. We assessed associations of 92 dietary factors with lung cancer risk in 327 790 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC). Cox regression yielded adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) per SD higher intake/day of each food/nutrient. Correction for multiple comparisons was performed using the false discovery rate and identified associations were evaluated in the Netherlands Cohort Study (NLCS). In EPIC, 2420 incident lung cancer cases were identified during a median of 15 years of follow-up. Higher intakes of fibre (HR per 1 SD higher intake/day = 0.91, 95% CI 0.87-0.96), fruit (HR = 0.91, 95% CI 0.86-0.96) and vitamin C (HR = 0.91, 95% CI 0.86-0.96) were associated with a lower risk of lung cancer, whereas offal (HR = 1.08, 95% CI 1.03-1.14), retinol (HR = 1.06, 95% CI 1.03-1.10) and beer/cider (HR = 1.04, 95% CI 1.02-1.07) intakes were positively associated with lung cancer risk. Associations did not differ by sex and there was less evidence for associations among never smokers. None of the six associations with overall lung cancer risk identified in EPIC were replicated in the NLCS (2861 cases), however in analyses of histological subtypes, inverse associations of fruit and vitamin C with squamous cell carcinoma were replicated in the NLCS. Overall, there is little evidence that intakes of specific foods and nutrients play a major role in primary lung cancer risk, but fruit and vitamin C intakes seem to be inversely associated with squamous cell lung cancer.

Associations of genetically predicted fatty acid levels across the phenome: A mendelian randomisation study.

BACKGROUND: Fatty acids are important dietary factors that have been extensively studied for their implication in health and disease. Evidence from epidemiological studies and randomised controlled trials on their role in cardiovascular, inflammatory, and other diseases remains inconsistent. The objective of this study was to assess whether genetically predicted fatty acid concentrations affect the risk of disease across a wide variety of clinical health outcomes. METHODS AND FINDINGS: The UK Biobank (UKB) is a large study involving over 500,000 participants aged 40 to 69 years at recruitment from 2006 to 2010. We used summary-level data for 117,143 UKB samples (base dataset), to extract genetic associations of fatty acids, and individual-level data for 322,232 UKB participants (target dataset) to conduct our discovery analysis. We studied potentially causal relationships of circulating fatty acids with 845 clinical diagnoses, using mendelian randomisation (MR) approach, within a phenome-wide association study (PheWAS) framework. Regression models in PheWAS were adjusted for sex, age, and the first 10 genetic principal components. External summary statistics were used for replication. When several fatty acids were associated with a health outcome, multivariable MR and MR-Bayesian method averaging (MR-BMA) was applied to disentangle their causal role. Genetic predisposition to higher docosahexaenoic acid (DHA) was associated with cholelithiasis and cholecystitis (odds ratio per mmol/L: 0.76, 95% confidence interval: 0.66 to 0.87). This was supported in replication analysis (FinnGen study) and by the genetically predicted omega-3 fatty acids analyses. Genetically predicted linoleic acid (LA), omega-6, polyunsaturated fatty acids (PUFAs), and total fatty acids (total FAs) showed positive associations with cardiovascular outcomes with support from replication analysis. Finally, higher genetically predicted levels of DHA (0.83, 0.73 to 0.95) and omega-3 (0.83, 0.75 to 0.92) were found to have a protective effect on obesity, which was supported using body mass index (BMI) in the GIANT consortium as replication analysis. Multivariable MR analysis suggested a direct detrimental effect of LA (1.64, 1.07 to 2.50) and omega-6 fatty acids (1.81, 1.06 to 3.09) on coronary heart disease (CHD). MR-BMA prioritised LA and omega-6 fatty acids as the top risk factors for CHD. Although we present a range of sensitivity analyses to the address MR assumptions, horizontal pleiotropy may still bias the reported associations and further evaluation in clinical trials is needed. CONCLUSIONS: Our study suggests potentially protective effects of circulating DHA and omega-3 concentrations on cholelithiasis and cholecystitis and on obesity, highlighting the need to further assess them as prevention treatments in clinical trials. Moreover, our findings do not support the supplementation of unsaturated fatty acids for cardiovascular disease prevention.

Associations of Mitochondrial and Nuclear Mitochondrial Variants and Genes with Seven Metabolic Traits.

Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear genes (MT-nDNA). In the CHARGEmtDNA+ Consortium, we studied genetic associations of mtDNA and MT-nDNA associations with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, and HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation and imputation of mtDNA variants was followed by single-variant and gene-based association testing. We report two significant common variants, one in MT-ATP6 associated (p ≤ 5E-04) with WHR and one in the D-loop with glucose. Five rare variants in MT-ATP6, MT-ND5, and MT-ND6 associated with BMI, WHR, or insulin. Gene-based meta-analysis identified MT-ND3 associated with BMI (p ≤ 1E-03). We considered 2,282 MT-nDNA candidate gene associations compiled from online summary results for our traits (20 unique studies with 31 dataset consortia's genome-wide associations [GWASs]). Of these, 109 genes associated (p ≤ 1E-06) with at least 1 of our 7 traits. We assessed regulatory features of variants in the 109 genes, cis- and trans-gene expression regulation, and performed enrichment and protein-protein interactions analyses. Of the identified mtDNA and MT-nDNA genes, 79 associated with adipose measures, 49 with glucose/insulin, 13 with risk for type 2 diabetes, and 18 with cardiovascular disease, indicating for pleiotropic effects with health implications. Additionally, 21 genes related to cholesterol, suggesting additional important roles for the genes identified. Our results suggest that mtDNA and MT-nDNA genes and variants reported make important contributions to glucose and insulin metabolism, adipocyte regulation, diabetes, and cardiovascular disease.

A Prospective Diet-Wide Association Study for Risk of Colorectal Cancer in EPIC.

BACKGROUND & AIMS: Evidence regarding the association of dietary exposures with colorectal cancer (CRC) risk is not consistent with a few exceptions. Therefore, we conducted a diet-wide association study (DWAS) in the European Prospective Investigation into Cancer and Nutrition (EPIC) to evaluate the associations between several dietary exposures with CRC risk. METHODS: The association of 92 food and nutrient intakes with CRC risk was assessed in 386,792 participants, 5069 of whom developed incident CRC. Correction for multiple comparisons was performed using the false discovery rate, and emerging associations were examined in the Netherlands Cohort Study (NLCS). Multiplicative gene-nutrient interactions were also tested in EPIC based on known CRC-associated loci. RESULTS: In EPIC, alcohol, liquor/spirits, wine, beer/cider, soft drinks, and pork were positively associated with CRC, whereas milk, cheese, calcium, phosphorus, magnesium, potassium, riboflavin, vitamin B6, beta carotene, fruit, fiber, nonwhite bread, banana, and total protein intakes were inversely associated. Of these 20 associations, 13 were replicated in the NLCS, for which a meta-analysis was performed, namely alcohol (summary hazard ratio [HR] per 1-SD increment in intake: 1.07; 95% confidence interval [CI], 1.04-1.09), liquor/spirits (HR per 1-SD increment in intake, 1.04; 95% CI, 1.02-1.06), wine (HR per 1-SD increment in intake, 1.04; 95% CI, 1.02-1.07), beer/cider (HR per 1-SD increment in intake, 1.06; 95% CI, 1.04-1.08), milk (HR per 1-SD increment in intake, 0.95; 95% CI, 0.93-0.98), cheese (HR per 1-SD increment in intake, 0.96; 95% CI, 0.94-0.99), calcium (HR per 1-SD increment in intake, 0.93; 95% CI, 0.90-0.95), phosphorus (HR per 1-SD increment in intake, 0.92; 95% CI, 0.90-0.95), magnesium (HR per 1-SD increment in intake, 0.95; 95% CI, 0.92-0.98), potassium (HR per 1-SD increment in intake, 0.96; 95% CI, 0.94-0.99), riboflavin (HR per 1-SD increment in intake, 0.94; 95% CI, 0.92-0.97), beta carotene (HR per 1-SD increment in intake, 0.96; 95% CI, 0.93-0.98), and total protein (HR per 1-SD increment in intake, 0.94; 95% CI, 0.92-0.97). None of the gene-nutrient interactions were significant after adjustment for multiple comparisons. CONCLUSIONS: Our findings confirm a positive association for alcohol and an inverse association for dairy products and calcium with CRC risk, and also suggest a lower risk at higher dietary intakes of phosphorus, magnesium, potassium, riboflavin, beta carotene, and total protein.

Finding Correspondence between Metabolomic Features in Untargeted Liquid Chromatography-Mass Spectrometry Metabolomics Datasets.

Integration of multiple datasets can greatly enhance bioanalytical studies, for example, by increasing power to discover and validate biomarkers. In liquid chromatography-mass spectrometry (LC-MS) metabolomics, it is especially hard to combine untargeted datasets since the majority of metabolomic features are not annotated and thus cannot be matched by chemical identity. Typically, the information available for each feature is retention time (RT), mass-to-charge ratio (m/z), and feature intensity (FI). Pairs of features from the same metabolite in separate datasets can exhibit small but significant differences, making matching very challenging. Current methods to address this issue are too simple or rely on assumptions that cannot be met in all cases. We present a method to find feature correspondence between two similar LC-MS metabolomics experiments or batches using only the features' RT, m/z, and FI. We demonstrate the method on both real and synthetic datasets, using six orthogonal validation strategies to gauge the matching quality. In our main example, 4953 features were uniquely matched, of which 585 (96.8%) of 604 manually annotated features were correct. In a second example, 2324 features could be uniquely matched, with 79 (90.8%) out of 87 annotated features correctly matched. Most of the missed annotated matches are between features that behave very differently from modeled inter-dataset shifts of RT, MZ, and FI. In a third example with simulated data with 4755 features per dataset, 99.6% of the matches were correct. Finally, the results of matching three other dataset pairs using our method are compared with a published alternative method, metabCombiner, showing the advantages of our approach. The method can be applied using M2S (Match 2 Sets), a free, open-source MATLAB toolbox, available at https://github.com/rjdossan/M2S.

Prognostic factors for adverse outcomes in patients with COVID-19: a field-wide systematic review and meta-analysis.

INTRODUCTION: The individual prognostic factors for coronavirus disease 2019 (COVID-19) are unclear. For this reason, we aimed to present a state-of-the-art systematic review and meta-analysis on the prognostic factors for adverse outcomes in COVID-19 patients. METHODS: We systematically reviewed PubMed from 1 January 2020 to 26 July 2020 to identify non-overlapping studies examining the association of any prognostic factor with any adverse outcome in patients with COVID-19. Random-effects meta-analysis was performed, and between-study heterogeneity was quantified using I2 statistic. Presence of small-study effects was assessed by applying the Egger's regression test. RESULTS: We identified 428 eligible articles, which were used in a total of 263 meta-analyses examining the association of 91 unique prognostic factors with 11 outcomes. Angiotensin-converting enzyme inhibitors, obstructive sleep apnoea, pharyngalgia, history of venous thromboembolism, sex, coronary heart disease, cancer, chronic liver disease, COPD, dementia, any immunosuppressive medication, peripheral arterial disease, rheumatological disease and smoking were associated with at least one outcome and had >1000 events, p<0.005, I2<50%, 95% prediction interval excluding the null value, and absence of small-study effects in the respective meta-analysis. The risk of bias assessment using the Quality in Prognosis Studies tool indicated high risk of bias in 302 out of 428 articles for study participation, 389 articles for adjustment for other prognostic factors and 396 articles for statistical analysis and reporting. CONCLUSIONS: Our findings could be used for prognostic model building and guide patient selection for randomised clinical trials.

Exploring the causal effect of maternal pregnancy adiposity on offspring adiposity: Mendelian randomisation using polygenic risk scores.

BACKGROUND: Greater maternal adiposity before or during pregnancy is associated with greater offspring adiposity throughout childhood, but the extent to which this is due to causal intrauterine or periconceptional mechanisms remains unclear. Here, we use Mendelian randomisation (MR) with polygenic risk scores (PRS) to investigate whether associations between maternal pre-/early pregnancy body mass index (BMI) and offspring adiposity from birth to adolescence are causal. METHODS: We undertook confounder adjusted multivariable (MV) regression and MR using mother-offspring pairs from two UK cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC) and Born in Bradford (BiB). In ALSPAC and BiB, the outcomes were birthweight (BW; N = 9339) and BMI at age 1 and 4 years (N = 8659 to 7575). In ALSPAC only we investigated BMI at 10 and 15 years (N = 4476 to 4112) and dual-energy X-ray absorptiometry (DXA) determined fat mass index (FMI) from age 10-18 years (N = 2659 to 3855). We compared MR results from several PRS, calculated from maternal non-transmitted alleles at between 29 and 80,939 single nucleotide polymorphisms (SNPs). RESULTS: MV and MR consistently showed a positive association between maternal BMI and BW, supporting a moderate causal effect. For adiposity at most older ages, although MV estimates indicated a strong positive association, MR estimates did not support a causal effect. For the PRS with few SNPs, MR estimates were statistically consistent with the null, but had wide confidence intervals so were often also statistically consistent with the MV estimates. In contrast, the largest PRS yielded MR estimates with narrower confidence intervals, providing strong evidence that the true causal effect on adolescent adiposity is smaller than the MV estimates (Pdifference = 0.001 for 15-year BMI). This suggests that the MV estimates are affected by residual confounding, therefore do not provide an accurate indication of the causal effect size. CONCLUSIONS: Our results suggest that higher maternal pre-/early-pregnancy BMI is not a key driver of higher adiposity in the next generation. Thus, they support interventions that target the whole population for reducing overweight and obesity, rather than a specific focus on women of reproductive age.

Genetically predicted circulating concentrations of micronutrients and risk of breast cancer: A Mendelian randomization study.

The epidemiological literature reports inconsistent associations between consumption or circulating concentrations of micronutrients and breast cancer risk. We investigated associations between genetically predicted concentrations of 11 micronutrients (beta-carotene, calcium, copper, folate, iron, magnesium, phosphorus, selenium, vitamin B6 , vitamin B12 and zinc) and breast cancer risk using Mendelian randomization (MR). A two-sample MR study was conducted using 122 977 women with breast cancer and 105 974 controls from the Breast Cancer Association Consortium. MR analyses were conducted using the inverse variance-weighted approach, and sensitivity analyses were conducted to assess the impact of potential violations of MR assumptions. A value of 1 SD (SD: 0.08 mmol/L) higher genetically predicted concentration of magnesium was associated with a 17% (odds ratio [OR]: 1.17, 95% confidence interval [CI]: 1.10-1.25, P value = 9.1 × 10-7 ) and 20% (OR: 1.20, 95% CI: 1.08-1.34, P value = 3.2 × 10-6 ) higher risk of overall and ER+ve breast cancer, respectively. An inverse association was observed for a SD (0.5 mg/dL) higher genetically predicted phosphorus concentration and ER-ve breast cancer (OR: 0.84, 95% CI: 0.72-0.98, P value = .03). There was little evidence that any other nutrient was associated with breast cancer. The results for magnesium were robust under all sensitivity analyses and survived correction for multiple comparisons. Higher circulating concentrations of magnesium and potentially phosphorus may affect breast cancer risk. Further work is required to replicate these findings and investigate underlying mechanisms.

Weight change in middle adulthood and risk of cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

Obesity is a risk factor for several major cancers. Associations of weight change in middle adulthood with cancer risk, however, are less clear. We examined the association of change in weight and body mass index (BMI) category during middle adulthood with 42 cancers, using multivariable Cox proportional hazards models in the European Prospective Investigation into Cancer and Nutrition cohort. Of 241 323 participants (31% men), 20% lost and 32% gained weight (>0.4 to 5.0 kg/year) during 6.9 years (average). During 8.0 years of follow-up after the second weight assessment, 20 960 incident cancers were ascertained. Independent of baseline BMI, weight gain (per one kg/year increment) was positively associated with cancer of the corpus uteri (hazard ratio [HR] = 1.14; 95% confidence interval: 1.05-1.23). Compared to stable weight (±0.4 kg/year), weight gain (>0.4 to 5.0 kg/year) was positively associated with cancers of the gallbladder and bile ducts (HR = 1.41; 1.01-1.96), postmenopausal breast (HR = 1.08; 1.00-1.16) and thyroid (HR = 1.40; 1.04-1.90). Compared to maintaining normal weight, maintaining overweight or obese BMI (World Health Organisation categories) was positively associated with most obesity-related cancers. Compared to maintaining the baseline BMI category, weight gain to a higher BMI category was positively associated with cancers of the postmenopausal breast (HR = 1.19; 1.06-1.33), ovary (HR = 1.40; 1.04-1.91), corpus uteri (HR = 1.42; 1.06-1.91), kidney (HR = 1.80; 1.20-2.68) and pancreas in men (HR = 1.81; 1.11-2.95). Losing weight to a lower BMI category, however, was inversely associated with cancers of the corpus uteri (HR = 0.40; 0.23-0.69) and colon (HR = 0.69; 0.52-0.92). Our findings support avoiding weight gain and encouraging weight loss in middle adulthood.

Validity of observational evidence on putative risk and protective factors: appraisal of 3744 meta-analyses on 57 topics.

BACKGROUND: The validity of observational studies and their meta-analyses is contested. Here, we aimed to appraise thousands of meta-analyses of observational studies using a pre-specified set of quantitative criteria that assess the significance, amount, consistency, and bias of the evidence. We also aimed to compare results from meta-analyses of observational studies against meta-analyses of randomized controlled trials (RCTs) and Mendelian randomization (MR) studies. METHODS: We retrieved from PubMed (last update, November 19, 2020) umbrella reviews including meta-analyses of observational studies assessing putative risk or protective factors, regardless of the nature of the exposure and health outcome. We extracted information on 7 quantitative criteria that reflect the level of statistical support, the amount of data, the consistency across different studies, and hints pointing to potential bias. These criteria were level of statistical significance (pre-categorized according to 10-6, 0.001, and 0.05 p-value thresholds), sample size, statistical significance for the largest study, 95% prediction intervals, between-study heterogeneity, and the results of tests for small study effects and for excess significance. RESULTS: 3744 associations (in 57 umbrella reviews) assessed by a median number of 7 (interquartile range 4 to 11) observational studies were eligible. Most associations were statistically significant at P < 0.05 (61.1%, 2289/3744). Only 2.6% of associations had P < 10-6, ≥1000 cases (or ≥20,000 participants for continuous factors), P < 0.05 in the largest study, 95% prediction interval excluding the null, and no large between-study heterogeneity, small study effects, or excess significance. Across the 57 topics, large heterogeneity was observed in the proportion of associations fulfilling various quantitative criteria. The quantitative criteria were mostly independent from one another. Across 62 associations assessed in both RCTs and in observational studies, 37.1% had effect estimates in opposite directions and 43.5% had effect estimates differing beyond chance in the two designs. Across 94 comparisons assessed in both MR and observational studies, such discrepancies occurred in 30.8% and 54.7%, respectively. CONCLUSIONS: Acknowledging that no gold-standard exists to judge whether an observational association is genuine, statistically significant results are common in observational studies, but they are rarely convincing or corroborated by randomized evidence.