Publications by authors named "Paul W Franks"

355 Publications

Associations between vitamin D levels and glucose metabolism markers among pregnant women and their infants in Puerto Rico.

Nutr Hosp 2021 Oct 14. Epub 2021 Oct 14.

Center for Clinical Research and Health Promotion. Medical Sciences Campus. University of Puerto Rico.

Objectives: low vitamin D during pregnancy is common and could adversely affect health outcomes. This study evaluated vitamin D status during pregnancy and early in life, and its association with glucose metabolism.

Methods: maternal serum 25(OH)D, glucose, and insulin levels were measured longitudinally during pregnancy in Hispanic women with overweight/obesity (n = 31) and their infants at birth and 4 months.

Results: insulin and HOMA-IR levels were higher among women with vitamin D below adequate levels compared to those with adequate levels in pregnancy (p < 0.05). Late in pregnancy, as vitamin D increased by one unit (ng/mL), insulin decreased by 0.44 units and HOMA-IR by 0.09 units. Maternal vitamin D late in pregnancy was correlated with infant vitamin D levels at birth (r = 0.89; p < 0.01) and 4 months (r = 0.9; p = 0.04), and with glucose (r = 0.79; p = 0.03) and insulin (r = 0.83; p = 0.04) at 4 months.

Conclusion: maternal vitamin D status was associated with maternal and infant glucose metabolism in this sample.
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http://dx.doi.org/10.20960/nh.03600DOI Listing
October 2021

Genomic editing of metformin efficacy-associated genetic variants in SLC47A1 does not alter SLC47A1 expression.

Hum Mol Genet 2021 Sep 9. Epub 2021 Sep 9.

Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, 20502, Sweden.

Several pharmacogenetics studies have identified an association between a greater metformin-dependent reduction in HbA1c levels and the minor A allele at rs2289669 in intron 10 of SLC47A1, encoding multidrug and toxin extrusion 1 (MATE1), a presumed metformin transporter. It is currently unknown if the rs2289669 locus is a cis-eQTL, which would validate its role as predictor of metformin efficacy. We looked at association between common genetic variants in the SLC47A1 gene region and HbA1c reduction after metformin treatment using locus-wise meta-analysis from the MetGen consortium. CRISPR-Cas9 was applied to perform allele editing of, or genomic deletion around, rs2289669 and of the closely linked rs8065082 in HepG2 cells. The genome-edited cells were evaluated for SLC47A1 expression and splicing. None of the common variants including rs2289669 showed significant association with metformin response. Genomic editing of either rs2289669 or rs8065082 did not alter SLC47A1 expression or splicing. Experimental and in silico analyses show that the rs2289669-containing haploblock does not appear to carry genetic variants that could explain its previously reported association with metformin efficacy.
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http://dx.doi.org/10.1093/hmg/ddab266DOI Listing
September 2021

Diet quality and risk and severity of COVID-19: a prospective cohort study.

Gut 2021 11 6;70(11):2096-2104. Epub 2021 Sep 6.

Clinical and Translational Epidemiological Unit, Massachusetts General Hospital, Boston, MA, USA

Objective: Poor metabolic health and unhealthy lifestyle factors have been associated with risk and severity of COVID-19, but data for diet are lacking. We aimed to investigate the association of diet quality with risk and severity of COVID-19 and its interaction with socioeconomic deprivation.

Design: We used data from 592 571 participants of the smartphone-based COVID-19 Symptom Study. Diet information was collected for the prepandemic period using a short food frequency questionnaire, and diet quality was assessed using a healthful Plant-Based Diet Score, which emphasises healthy plant foods such as fruits or vegetables. Multivariable Cox models were fitted to calculate HRs and 95% CIs for COVID-19 risk and severity defined using a validated symptom-based algorithm or hospitalisation with oxygen support, respectively.

Results: Over 3 886 274 person-months of follow-up, 31 815 COVID-19 cases were documented. Compared with individuals in the lowest quartile of the diet score, high diet quality was associated with lower risk of COVID-19 (HR 0.91; 95% CI 0.88 to 0.94) and severe COVID-19 (HR 0.59; 95% CI 0.47 to 0.74). The joint association of low diet quality and increased deprivation on COVID-19 risk was higher than the sum of the risk associated with each factor alone (P=0.005). The corresponding absolute excess rate per 10 000 person/months for lowest vs highest quartile of diet score was 22.5 (95% CI 18.8 to 26.3) among persons living in areas with low deprivation and 40.8 (95% CI 31.7 to 49.8) among persons living in areas with high deprivation.

Conclusions: A diet characterised by healthy plant-based foods was associated with lower risk and severity of COVID-19. This association may be particularly evident among individuals living in areas with higher socioeconomic deprivation.
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http://dx.doi.org/10.1136/gutjnl-2021-325353DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8500931PMC
November 2021

Distinct Molecular Signatures of Clinical Clusters in People with Type 2 Diabetes: an IMIRHAPSODY Study.

Diabetes 2021 Aug 10. Epub 2021 Aug 10.

Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, CRC, Lund University, SUS, Malmö, Sweden.

Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity a previous study clustered people with diabetes into five diabetes subtypes. The aim of the current study is to investigate the aetiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic- (N=12828), metabolomic- (N=2945), lipidomic- (N=2593) and proteomic (N=1170) data were obtained in plasma. In each datatype each cluster was compared with the other four clusters as the reference. The insulin resistant cluster showed the most distinct molecular signature, with higher BCAAs, DAG and TAG levels and aberrant protein levels in plasma enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher cytokines. A subset of the mild diabetes cluster with high HDL showed the most beneficial molecular profile with opposite effects to those seen in the insulin resistant cluster. This study showed that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease.
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http://dx.doi.org/10.2337/db20-1281DOI Listing
August 2021

Modest effects of dietary supplements during the COVID-19 pandemic: insights from 445 850 users of the COVID-19 Symptom Study app.

BMJ Nutr Prev Health 2021 19;4(1):149-157. Epub 2021 Apr 19.

Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.

Objectives: Dietary supplements may ameliorate SARS-CoV-2 infection, although scientific evidence to support such a role is lacking. We investigated whether users of the COVID-19 Symptom Study app who regularly took dietary supplements were less likely to test positive for SARS-CoV-2 infection.

Design: App-based community survey.

Setting: 445 850 subscribers of an app that was launched to enable self-reported information related to SARS-CoV-2 infection for use in the general population in the UK (n=372 720), the USA (n=45 757) and Sweden (n=27 373).

Main Exposure: Self-reported regular dietary supplement usage (constant use during previous 3 months) in the first waves of the pandemic up to 31 July 2020.

Main Outcome Measures: SARS-CoV-2 infection confirmed by viral RNA reverse transcriptase PCR test or serology test before 31 July 2020.

Results: In 372 720 UK participants (175 652 supplement users and 197 068 non-users), those taking probiotics, omega-3 fatty acids, multivitamins or vitamin D had a lower risk of SARS-CoV-2 infection by 14% (95% CI (8% to 19%)), 12% (95% CI (8% to 16%)), 13% (95% CI (10% to 16%)) and 9% (95% CI (6% to 12%)), respectively, after adjusting for potential confounders. No effect was observed for those taking vitamin C, zinc or garlic supplements. On stratification by sex, age and body mass index (BMI), the protective associations in individuals taking probiotics, omega-3 fatty acids, multivitamins and vitamin D were observed in females across all ages and BMI groups, but were not seen in men. The same overall pattern of association was observed in both the US and Swedish cohorts.

Conclusion: In women, we observed a modest but significant association between use of probiotics, omega-3 fatty acid, multivitamin or vitamin D supplements and lower risk of testing positive for SARS-CoV-2. We found no clear benefits for men nor any effect of vitamin C, garlic or zinc. Randomised controlled trials are required to confirm these observational findings before any therapeutic recommendations can be made.
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http://dx.doi.org/10.1136/bmjnph-2021-000250DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8061565PMC
April 2021

Mortality risk comparing walking pace to handgrip strength and a healthy lifestyle: A UK Biobank study.

Eur J Prev Cardiol 2021 Jul;28(7):704-712

Diabetes Research Centre, University of Leicester, UK.

Aims: Brisk walking and a greater muscle strength have been associated with a longer life; whether these associations are influenced by other lifestyle behaviours, however, is less well known.

Methods: Information on usual walking pace (self-defined as slow, steady/average, or brisk), dynamometer-assessed handgrip strength, lifestyle behaviours (physical activity, TV viewing, diet, alcohol intake, sleep and smoking) and body mass index was collected at baseline in 450,888 UK Biobank study participants. We estimated 10-year standardised survival for individual and combined lifestyle behaviours and body mass index across levels of walking pace and handgrip strength.

Results: Over a median follow-up of 7.0 years, 3808 (1.6%) deaths in women and 6783 (3.2%) in men occurred. Brisk walkers had a survival advantage over slow walkers, irrespective of the degree of engagement in other lifestyle behaviours, except for smoking. Estimated 10-year survival was higher in brisk walkers who otherwise engaged in an unhealthy lifestyle compared to slow walkers who engaged in an otherwise healthy lifestyle: 97.1% (95% confidence interval: 96.9-97.3) vs 95.0% (94.6-95.4) in women; 94.8% (94.7-95.0) vs 93.7% (93.3-94.2) in men. Body mass index modified the association between walking pace and survival in men, with the largest survival benefits of brisk walking observed in underweight participants. Compared to walking pace, for handgrip strength there was more overlap in 10-year survival across lifestyle behaviours.

Conclusion: Except for smoking, brisk walkers with an otherwise unhealthy lifestyle have a lower mortality risk than slow walkers with an otherwise healthy lifestyle.
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http://dx.doi.org/10.1177/2047487319885041DOI Listing
July 2021

Profiles of Glucose Metabolism in Different Prediabetes Phenotypes, Classified by Fasting Glycemia, 2-Hour OGTT, Glycated Hemoglobin, and 1-Hour OGTT: An IMI DIRECT Study.

Diabetes 2021 Sep 7;70(9):2092-2106. Epub 2021 Jul 7.

Department of Epidemiology and Data Science, Amsterdam Medical Centre, location VUMC, Amsterdam, the Netherlands.

Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants ( = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). β-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISR), and insulin secretion potentiation ( < 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISR ( < 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, < 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.
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http://dx.doi.org/10.2337/db21-0227DOI Listing
September 2021

Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study.

Diabetologia 2021 Sep 10;64(9):1982-1989. Epub 2021 Jun 10.

Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.

Aims/hypothesis: Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes. In the current study we replicate and cross-validate these type 2 diabetes clusters in three large cohorts using variables readily measured in the clinic.

Methods: In three independent cohorts, in total 15,940 individuals were clustered based on age, BMI, HbA, random or fasting C-peptide, and HDL-cholesterol. Clusters were cross-validated against the original clusters based on HOMA measures. In addition, between cohorts, clusters were cross-validated by re-assigning people based on each cohort's cluster centres. Finally, we compared the time to insulin requirement for each cluster.

Results: Five distinct type 2 diabetes clusters were identified and mapped back to the original four All New Diabetics in Scania (ANDIS) clusters. Using C-peptide and HDL-cholesterol instead of HOMA2-B and HOMA2-IR, three of the clusters mapped with high sensitivity (80.6-90.7%) to the previously identified severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD) and mild obesity-related diabetes (MOD) clusters. The previously described ANDIS mild age-related diabetes (MARD) cluster could be mapped to the two milder groups in our study: one characterised by high HDL-cholesterol (mild diabetes with high HDL-cholesterol [MDH] cluster), and the other not having any extreme characteristic (mild diabetes [MD]). When these two milder groups were combined, they mapped well to the previously labelled MARD cluster (sensitivity 79.1%). In the cross-validation between cohorts, particularly the SIDD and MDH clusters cross-validated well, with sensitivities ranging from 73.3% to 97.1%. SIRD and MD showed a lower sensitivity, ranging from 36.1% to 92.3%, where individuals shifted from SIRD to MD and vice versa. People belonging to the SIDD cluster showed the fastest progression towards insulin requirement, while the MDH cluster showed the slowest progression.

Conclusions/interpretation: Clusters based on C-peptide instead of HOMA2 measures resemble those based on HOMA2 measures, especially for SIDD, SIRD and MOD. By adding HDL-cholesterol, the MARD cluster based upon HOMA2 measures resulted in the current clustering into two clusters, with one cluster having high HDL levels. Cross-validation between cohorts showed generally a good resemblance between cohorts. Together, our results show that the clustering based on clinical variables readily measured in the clinic (age, HbA, HDL-cholesterol, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts. Adding HDL-cholesterol to the clustering resulted in the identification of a cluster with very slow glycaemic deterioration.
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http://dx.doi.org/10.1007/s00125-021-05490-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8382625PMC
September 2021

Meal-induced inflammation: postprandial insights from the Personalised REsponses to DIetary Composition Trial (PREDICT) study in 1000 participants.

Am J Clin Nutr 2021 09;114(3):1028-1038

Department of Nutritional Sciences, King's College London, London, United Kingdom.

Background: Meal-induced metabolic changes trigger an acute inflammatory response, contributing to chronic inflammation and associated diseases.

Objectives: We aimed to characterize variability in postprandial inflammatory responses using traditional (IL-6) and novel [glycoprotein acetylation (GlycA)] biomarkers of inflammation and dissect their biological determinants with a focus on postprandial glycemia and lipemia.

Methods: Postprandial (0-6 h) glucose, triglyceride (TG), IL-6, and GlycA responses were measured at multiple intervals after sequential mixed-nutrient meals (0 h and 4 h) in 1002 healthy adults aged 18-65 y from the PREDICT (Personalised REsponses to DIetary Composition Trial) 1 study, a single-arm dietary intervention study. Measures of habitual diet, blood biochemistry, gut microbiome composition, and visceral fat mass (VFM) were also collected.

Results: The postprandial changes in GlycA and IL-6 concentrations were highly variable between individuals. Participants eliciting an increase in GlycA and IL-6 (60% and 94% of the total participants, respectively) had mean 6-h increases of 11% and 190%, respectively. Peak postprandial TG and glucose concentrations were significantly associated with 6-h GlycA (r = 0.83 and r = 0.24, respectively; both P < 0.001) but not with 6-h IL-6 (both P > 0.26). A random forest model revealed the maximum TG concentration was the strongest postprandial TG predictor of postprandial GlycA and structural equation modeling revealed that VFM and fasting TG were most strongly associated with fasting and postprandial GlycA. Network Mendelian randomization demonstrated a causal link between VFM and fasting GlycA, mediated (28%) by fasting TG. Individuals eliciting enhanced GlycA responses had higher predicted cardiovascular disease risk (using the atherosclerotic disease risk score) than the rest of the cohort.

Conclusions: The variable postprandial increases in GlycA and their associations with TG metabolism highlight the importance of modulating TG in concert with obesity to reduce GlycA and associated low-grade inflammation-related diseases.This trial was registered at clinicaltrials.gov as NCT03479866.
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http://dx.doi.org/10.1093/ajcn/nqab132DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8408875PMC
September 2021

The trans-ancestral genomic architecture of glycemic traits.

Nat Genet 2021 06 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

Postprandial glycaemic dips predict appetite and energy intake in healthy individuals.

Nat Metab 2021 04 12;3(4):523-529. Epub 2021 Apr 12.

Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.

Understanding how to modulate appetite in humans is key to developing successful weight loss interventions. Here, we showed that postprandial glucose dips 2-3 h after a meal are a better predictor of postprandial self-reported hunger and subsequent energy intake than peak glucose at 0-2 h and glucose incremental area under the blood glucose curve at 0-2 h. We explore the links among postprandial glucose, appetite and subsequent energy intake in 1,070 participants from a UK exploratory and US validation cohort, who consumed 8,624 standardized meals followed by 71,715 ad libitum meals, using continuous glucose monitors to record postprandial glycaemia. For participants eating each of the standardized meals, the average postprandial glucose dip at 2-3 h relative to baseline level predicted an increase in hunger at 2-3 h (r = 0.16, P < 0.001), shorter time until next meal (r = -0.14, P < 0.001), greater energy intake at 3-4 h (r = 0.19, P < 0.001) and greater energy intake at 24 h (r = 0.27, P < 0.001). Results were directionally consistent in the US validation cohort. These data provide a quantitative assessment of the relevance of postprandial glycaemia in appetite and energy intake modulation.
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http://dx.doi.org/10.1038/s42255-021-00383-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610681PMC
April 2021

Symptoms and syndromes associated with SARS-CoV-2 infection and severity in pregnant women from two community cohorts.

Sci Rep 2021 03 25;11(1):6928. Epub 2021 Mar 25.

School of Biomedical Engineering and Imaging Sciences, King's College London, 9th floor, Becket House, 1 Lambeth Palace Road, London, SE1 7EU, UK.

We tested whether pregnant and non-pregnant women differ in COVID-19 symptom profile and severity, and we extended previous investigations on hospitalized pregnant women to those who did not require hospitalization. Two female community-based cohorts (18-44 years) provided longitudinal (smartphone application, N = 1,170,315, n = 79 pregnant tested positive) and cross-sectional (web-based survey, N = 1,344,966, n = 134 pregnant tested positive) data, prospectively collected through self-participatory citizen surveillance in UK, Sweden and USA. Pregnant and non-pregnant were compared for frequencies of events, including SARS-CoV-2 testing, symptoms and hospitalization rates. Multivariable regression was used to investigate symptoms severity and comorbidity effects. Pregnant and non-pregnant women positive for SARS-CoV-2 infection were not different in syndromic severity, except for gastrointestinal symptoms. Pregnant were more likely to have received testing, despite reporting fewer symptoms. Pre-existing lung disease was most closely associated with syndromic severity in pregnant hospitalized. Heart and kidney diseases and diabetes increased risk. The most frequent symptoms among non-hospitalized women were anosmia [63% pregnant, 92% non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant who were hospitalized. Consistent with observations in non-pregnant populations, lung disease and diabetes were associated with increased risk of more severe SARS-CoV-2 infection during pregnancy.
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http://dx.doi.org/10.1038/s41598-021-86452-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7994587PMC
March 2021

Symptom clusters in COVID-19: A potential clinical prediction tool from the COVID Symptom Study app.

Sci Adv 2021 03 19;7(12). Epub 2021 Mar 19.

Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, MA, USA.

As no one symptom can predict disease severity or the need for dedicated medical support in coronavirus disease 2019 (COVID-19), we asked whether documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations. Clustering was validated on an independent replication dataset between 1 and 28 May 2020. Using the first 5 days of symptom logging, the ROC-AUC (receiver operating characteristic - area under the curve) of need for respiratory support was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required.
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http://dx.doi.org/10.1126/sciadv.abd4177DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7978420PMC
March 2021

Blue poo: impact of gut transit time on the gut microbiome using a novel marker.

Gut 2021 Sep 15;70(9):1665-1674. Epub 2021 Mar 15.

Diabetes and Nutritional Sciences Division, King's College London, London, UK

Background And Aims: Gut transit time is a key modulator of host-microbiome interactions, yet this is often overlooked, partly because reliable methods are typically expensive or burdensome. The aim of this single-arm, single-blinded intervention study is to assess (1) the relationship between gut transit time and the human gut microbiome, and (2) the utility of the 'blue dye' method as an inexpensive and scalable technique to measure transit time.

Methods: We assessed interactions between the taxonomic and functional potential profiles of the gut microbiome (profiled via shotgun metagenomic sequencing), gut transit time (measured via the blue dye method), cardiometabolic health and diet in 863 healthy individuals from the PREDICT 1 study.

Results: We found that gut microbiome taxonomic composition can accurately discriminate between gut transit time classes (0.82 area under the receiver operating characteristic curve) and longer gut transit time is linked with specific microbial species such as , spp and spp (false discovery rate-adjusted p values <0.01). The blue dye measure of gut transit time had the strongest association with the gut microbiome over typical transit time proxies such as stool consistency and frequency.

Conclusions: Gut transit time, measured via the blue dye method, is a more informative marker of gut microbiome function than traditional measures of stool consistency and frequency. The blue dye method can be applied in large-scale epidemiological studies to advance diet-microbiome-health research. Clinical trial registry website https://clinicaltrials.gov/ct2/show/NCT03479866 and trial number NCT03479866.
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http://dx.doi.org/10.1136/gutjnl-2020-323877DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349893PMC
September 2021

Attributes and predictors of long COVID.

Nat Med 2021 04 10;27(4):626-631. Epub 2021 Mar 10.

Zoe Global, London, UK.

Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called 'long COVID', are rising but little is known about prevalence, risk factors or whether it is possible to predict a protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app. A total of 558 (13.3%) participants reported symptoms lasting ≥28 days, 189 (4.5%) for ≥8 weeks and 95 (2.3%) for ≥12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76-4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services.
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http://dx.doi.org/10.1038/s41591-021-01292-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611399PMC
April 2021

Racial and ethnic differences in COVID-19 vaccine hesitancy and uptake.

medRxiv 2021 Feb 28. Epub 2021 Feb 28.

Background: Racial and ethnic minorities have been disproportionately impacted by COVID-19. In the initial phase of population-based vaccination in the United States (U.S.) and United Kingdom (U.K.), vaccine hesitancy and limited access may result in disparities in uptake.

Methods: We performed a cohort study among U.S. and U.K. participants in the smartphone-based COVID Symptom Study (March 24, 2020-February 16, 2021). We used logistic regression to estimate odds ratios (ORs) of COVID-19 vaccine hesitancy (unsure/not willing) and receipt.

Results: In the U.S. ( =87,388), compared to White non-Hispanic participants, the multivariable ORs of vaccine hesitancy were 3.15 (95% CI: 2.86 to 3.47) for Black participants, 1.42 (1.28 to 1.58) for Hispanic participants, 1.34 (1.18 to 1.52) for Asian participants, and 2.02 (1.70 to 2.39) for participants reporting more than one race/other. In the U.K. ( =1,254,294), racial and ethnic minorities had similarly elevated hesitancy: compared to White participants, their corresponding ORs were 2.84 (95% CI: 2.69 to 2.99) for Black participants, 1.66 (1.57 to 1.76) for South Asian participants, 1.84 (1.70 to 1.98) for Middle East/East Asian participants, and 1.48 (1.39 to 1.57) for participants reporting more than one race/other. Among U.S. participants, the OR of vaccine receipt was 0.71 (0.64 to 0.79) for Black participants, a disparity that persisted among individuals who specifically endorsed a willingness to obtain a vaccine. In contrast, disparities in uptake were not observed in the U.K.

Conclusions: COVID-19 vaccine hesitancy was greater among racial and ethnic minorities, and Black participants living in the U.S. were less likely to receive a vaccine than White participants. Lower uptake among Black participants in the U.S. during the initial vaccine rollout is attributable to both hesitancy and disparities in access.
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http://dx.doi.org/10.1101/2021.02.25.21252402DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924296PMC
February 2021

Monogenic Diabetes: From Genetic Insights to Population-Based Precision in Care. Reflections From a Editors' Expert Forum.

Diabetes Care 2020 12;43(12):3117-3128

Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.

Individualization of therapy based on a person's specific type of diabetes is one key element of a "precision medicine" approach to diabetes care. However, applying such an approach remains difficult because of barriers such as disease heterogeneity, difficulties in accurately diagnosing different types of diabetes, multiple genetic influences, incomplete understanding of pathophysiology, limitations of current therapies, and environmental, social, and psychological factors. Monogenic diabetes, for which single gene mutations are causal, is the category most suited to a precision approach. The pathophysiological mechanisms of monogenic diabetes are understood better than those of any other form of diabetes. Thus, this category offers the advantage of accurate diagnosis of nonoverlapping etiological subgroups for which specific interventions can be applied. Although representing a small proportion of all diabetes cases, monogenic forms present an opportunity to demonstrate the feasibility of precision medicine strategies. In June 2019, the editors of convened a panel of experts to discuss this opportunity. This article summarizes the major themes that arose at that forum. It presents an overview of the common causes of monogenic diabetes, describes some challenges in identifying and treating these disorders, and reports experience with various approaches to screening, diagnosis, and management. This article complements a larger American Diabetes Association effort supporting implementation of precision medicine for monogenic diabetes, which could serve as a platform for a broader initiative to apply more precise tactics to treating the more common forms of diabetes.
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http://dx.doi.org/10.2337/dci20-0065DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8162450PMC
December 2020

LRIG proteins regulate lipid metabolism via BMP signaling and affect the risk of type 2 diabetes.

Commun Biol 2021 01 19;4(1):90. Epub 2021 Jan 19.

Department of Radiation Sciences, Oncology, Umeå University, SE-90187, Umeå, Sweden.

Leucine-rich repeats and immunoglobulin-like domains (LRIG) proteins have been implicated as regulators of growth factor signaling; however, the possible redundancy among mammalian LRIG1, LRIG2, and LRIG3 has hindered detailed elucidation of their physiological functions. Here, we show that Lrig-null mouse embryonic fibroblasts (MEFs) are deficient in adipogenesis and bone morphogenetic protein (BMP) signaling. In contrast, transforming growth factor-beta (TGF-β) and receptor tyrosine kinase (RTK) signaling appeared unaltered in Lrig-null cells. The BMP signaling defect was rescued by ectopic expression of LRIG1 or LRIG3 but not by expression of LRIG2. Caenorhabditis elegans with mutant LRIG/sma-10 variants also exhibited a lipid storage defect. Human LRIG1 variants were strongly associated with increased body mass index (BMI) yet protected against type 2 diabetes; these effects were likely mediated by altered adipocyte morphology. These results demonstrate that LRIG proteins function as evolutionarily conserved regulators of lipid metabolism and BMP signaling and have implications for human disease.
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http://dx.doi.org/10.1038/s42003-020-01613-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815736PMC
January 2021

Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals.

Nat Med 2021 02 11;27(2):321-332. Epub 2021 Jan 11.

Zoe Global Ltd, London, UK.

The gut microbiome is shaped by diet and influences host metabolism; however, these links are complex and can be unique to each individual. We performed deep metagenomic sequencing of 1,203 gut microbiomes from 1,098 individuals enrolled in the Personalised Responses to Dietary Composition Trial (PREDICT 1) study, whose detailed long-term diet information, as well as hundreds of fasting and same-meal postprandial cardiometabolic blood marker measurements were available. We found many significant associations between microbes and specific nutrients, foods, food groups and general dietary indices, which were driven especially by the presence and diversity of healthy and plant-based foods. Microbial biomarkers of obesity were reproducible across external publicly available cohorts and in agreement with circulating blood metabolites that are indicators of cardiovascular disease risk. While some microbes, such as Prevotella copri and Blastocystis spp., were indicators of favorable postprandial glucose metabolism, overall microbiome composition was predictive for a large panel of cardiometabolic blood markers including fasting and postprandial glycemic, lipemic and inflammatory indices. The panel of intestinal species associated with healthy dietary habits overlapped with those associated with favorable cardiometabolic and postprandial markers, indicating that our large-scale resource can potentially stratify the gut microbiome into generalizable health levels in individuals without clinically manifest disease.
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http://dx.doi.org/10.1038/s41591-020-01183-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353542PMC
February 2021

Lifestyle Intervention in Pregnant Women With Obesity Impacts Cord Blood DNA Methylation, Which Associates With Body Composition in the Offspring.

Diabetes 2021 04 11;70(4):854-866. Epub 2021 Jan 11.

Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden

Maternal obesity may lead to epigenetic alterations in the offspring and might thereby contribute to disease later in life. We investigated whether a lifestyle intervention in pregnant women with obesity is associated with epigenetic variation in cord blood and body composition in the offspring. Genome-wide DNA methylation was analyzed in cord blood from 208 offspring from the Treatment of Obese Pregnant women (TOP)-study, which includes pregnant women with obesity randomized to lifestyle interventions comprised of physical activity with or without dietary advice versus control subjects (standard of care). DNA methylation was altered at 379 sites, annotated to 370 genes, in cord blood from offspring of mothers following a lifestyle intervention versus control subjects (false discovery rate [FDR] <5%) when using the Houseman reference-free method to correct for cell composition, and three of these sites were significant based on Bonferroni correction. These 370 genes are overrepresented in gene ontology terms, including response to fatty acids and adipose tissue development. Offspring of mothers included in a lifestyle intervention were born with more lean mass compared with control subjects. Methylation at 17 sites, annotated to, for example, , , , and , partially mediates the effect of the lifestyle intervention on lean mass in the offspring (FDR <5%). Moreover, 22 methylation sites were associated with offspring BMI scores during the first 3 years of life ( < 0.05). Overall, lifestyle interventions in pregnant women with obesity are associated with epigenetic changes in offspring, potentially influencing the offspring's lean mass and early growth.
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http://dx.doi.org/10.2337/db20-0487DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7980200PMC
April 2021

Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.

Nat Commun 2021 01 5;12(1):24. Epub 2021 Jan 5.

Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA.

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
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http://dx.doi.org/10.1038/s41467-020-19366-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785747PMC
January 2021

Author Correction: An investigation of causal relationships between prediabetes and vascular complications.

Nat Commun 2021 Jan 4;12(1):202. Epub 2021 Jan 4.

Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre, Lund University, Skåne University Hospital, Jan Waldenströms gata 35, Malmö, SE-20502, Sweden.

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http://dx.doi.org/10.1038/s41467-020-20663-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7782799PMC
January 2021

Interaction of diabetes genetic risk and successful lifestyle modification in the Diabetes Prevention Programme.

Diabetes Obes Metab 2021 04 29;23(4):1030-1040. Epub 2021 Jan 29.

Centre for Lifecourse Epidemiology of Adiposity and Diabetes, Colorado School of Public Health, Aurora, Colorado, USA.

Aim: To test whether diabetes genetic risk modifies the association of successful lifestyle changes with incident diabetes.

Materials And Methods: We studied 823 individuals randomized to the intensive lifestyle intervention (ILS) arm of the Diabetes Prevention Programme who were diabetes-free 1 year after enrolment. We tested additive and multiplicative interactions of a 67-variant diabetes genetic risk score (GRS) with achievement of three ILS goals at 1 year (≥7% weight loss, ≥150 min/wk of moderate leisure-time physical activity, and/or a goal for self-reported total fat intake) on the primary outcome of incident diabetes over 3 years of follow-up.

Results: A lower GRS and achieving each or all three ILS goals were each associated with lower incidence of diabetes (all P < 0.05). Additive interactions were significant between the GRS and achievement of the weight loss goal (P < 0.001), physical activity goal (P = 0.02), and all three ILS goals (P < 0.001) for diabetes risk. Achievement of all three ILS goals was associated with 1.8 (95% CI 0.3, 3.4), 3.1 (95% CI 1.5, 4.7), and 3.9 (95% CI 1.6, 6.2) fewer diabetes cases/100-person-years in the first, second and third GRS tertiles (P < 0.001 for trend). Multiplicative interactions between the GRS and ILS goal achievement were significant for the diet goal (P < 0.001), but not for weight loss (P = 0.18) or physical activity (P = 0.62) goals.

Conclusions: Genetic risk may identify high-risk subgroups for whom successful lifestyle modification is associated with greater absolute reduction in the risk of incident diabetes.
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http://dx.doi.org/10.1111/dom.14309DOI Listing
April 2021

Processes Underlying Glycemic Deterioration in Type 2 Diabetes: An IMI DIRECT Study.

Diabetes Care 2021 02 15;44(2):511-518. Epub 2020 Dec 15.

Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark.

Objective: We investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D).

Research Design And Methods: A total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), β-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression.

Results: Faster HbA progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles ( = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8-10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07-0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role.

Conclusions: Deteriorating insulin sensitivity and β-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, β-cell function, and insulin clearance may be relevant to prevent progression.
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http://dx.doi.org/10.2337/dc20-1567DOI Listing
February 2021

Detecting COVID-19 infection hotspots in England using large-scale self-reported data from a mobile application: a prospective, observational study.

Lancet Public Health 2021 01 3;6(1):e21-e29. Epub 2020 Dec 3.

School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Background: As many countries seek to slow the spread of COVID-19 without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention.

Methods: In this prospective, observational study, we did modelling using longitudinal, self-reported data from users of the COVID Symptom Study app in England between March 24, and Sept 29, 2020. Beginning on April 28, in England, the Department of Health and Social Care allocated RT-PCR tests for COVID-19 to app users who logged themselves as healthy at least once in 9 days and then reported any symptom. We calculated incidence of COVID-19 using the invited swab (RT-PCR) tests reported in the app, and we estimated prevalence using a symptom-based method (using logistic regression) and a method based on both symptoms and swab test results. We used incidence rates to estimate the effective reproduction number, R(t), modelling the system as a Poisson process and using Markov Chain Monte-Carlo. We used three datasets to validate our models: the Office for National Statistics (ONS) Community Infection Survey, the Real-time Assessment of Community Transmission (REACT-1) study, and UK Government testing data. We used geographically granular estimates to highlight regions with rapidly increasing case numbers, or hotspots.

Findings: From March 24 to Sept 29, 2020, a total of 2 873 726 users living in England signed up to use the app, of whom 2 842 732 (98·9%) provided valid age information and daily assessments. These users provided a total of 120 192 306 daily reports of their symptoms, and recorded the results of 169 682 invited swab tests. On a national level, our estimates of incidence and prevalence showed a similar sensitivity to changes to those reported in the ONS and REACT-1 studies. On Sept 28, 2020, we estimated an incidence of 15 841 (95% CI 14 023-17 885) daily cases, a prevalence of 0·53% (0·45-0·60), and R(t) of 1·17 (1·15-1·19) in England. On a geographically granular level, on Sept 28, 2020, we detected 15 (75%) of the 20 regions with highest incidence according to government test data.

Interpretation: Our method could help to detect rapid case increases in regions where government testing provision is lower. Self-reported data from mobile applications can provide an agile resource to inform policy makers during a quickly moving pandemic, serving as a complementary resource to more traditional instruments for disease surveillance.

Funding: Zoe Global, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK National Institute for Health Research, UK Medical Research Council and British Heart Foundation, Alzheimer's Society, Chronic Disease Research Foundation.
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http://dx.doi.org/10.1016/S2468-2667(20)30269-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785969PMC
January 2021
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