Interaction of melatonin receptor 1B (MTNR1B) genotype and type of breakfast (protein-enriched v carbohydrate-rich) on postprandial glucose response: a randomised crossover trial.

Interaction of melatonin receptor 1B (MTNR1B) genotype and type of breakfast (protein-enriched v carbohydrate-rich) on postprandial glucose response: a randomised crossover trial. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Interaction of melatonin receptor 1B (MTNR1B) genotype and type of breakfast (protein-enriched v carbohydrate-rich) on postprandial glucose response: a randomised crossover trial. Alexandra King, Yiannis Mavrommatis, Jonathan Nixon, Angeliki Kapellou, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8678875/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background The risk allele (G) of MTNR1B rs10830963 has been associated with impaired glucose tolerance, increased fasting glucose and type 2 diabetes (T2D). Late evening eating, when endogenous melatonin levels are elevated, is associated with impaired glucose control in MTNR1B risk carriers. Endogenous melatonin levels remain elevated into the morning so may influence glucose response to breakfast. Objective To investigate the interaction of MTNR1B genotype and type of breakfast on postprandial glucose response. Methods Following an overnight fast, participants consumed either a standard carbohydrate-rich or protein-enriched porridge breakfast. Post-prandial glucose levels were recorded for two hours using a continuous glucose monitor (CGM). One week later, participants repeated the protocol consuming the alternate breakfast. A two-way mixed ANOVA determined the effect of breakfast and genotype on post-prandial glucose levels. Results Fifty-four adults completed the study. Fasting glucose was significantly higher (p = 0.008) in GG (5.53 ± 0.43 mmol/L) compared to CC or CG participants (5.02 ± 0.42 and 5.19 ± 0.52 mmol/L). Post-prandial iAUC was significantly greater following the carbohydrate-rich breakfast compared to the protein-enriched breakfast (p < 0.001). Following the carbohydrate-rich breakfast iAUC was significantly greater in GG participants compared to CC (p = 0.026) and CG participants (p = 0.029). There was no significant difference between genotype groups following the protein-enriched breakfast (p > 0.05). Conclusion The study findings demonstrate, in a relatively young and healthy population, MTNR1B genotype significantly affects markers associated with T2D risk. Personalised genotype-based advice to adjust timing and composition of meals consumed when endogenous melatonin levels are increased may reduce subsequent T2D risk. Health sciences/Diseases/Endocrine system and metabolic diseases/Diabetes/Type 2 diabetes Biological sciences/Genetics/Population genetics/Genetic variation Type 2 diabetes MTNR1B genotype postprandial glucose breakfast Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Melatonin is a circadian hormone, synthesis and release of melatonin are inhibited by daytime light. Consequently, levels of melatonin fluctuate over the 24h day, increasing during the evening, peaking in the early hours of the morning and then reducing( 1 , 2 ). In addition to sleep quality and circadian regulation, melatonin is linked to glucose metabolism. Melatonin mediates insulin secretion in pancreatic β-cells via the G protein-coupled melatonin receptors (MT1 and MT2). Binding of melatonin to MT1 and MT2 inhibits cyclic adenosine monophosphate and cyclic guanine monophosphate signalling causing decreased insulin secretion( 2 ). Furthermore, studies have demonstrated that administration of exogenous melatonin (1-5mg) prior to an oral glucose tolerance test (OGTT) results in a significantly greater glucose response( 3 , 4 ). The melatonin receptor 1B ( MTNR1B ) gene codes for the MT2 receptor and is expressed in a number of tissues including the pancreas( 5 ). A variation in the MTNR1B gene rs10830963 is associated with increased expression of MT2 in islet cells of people with the risk (G) allele( 6 ). In an analysis of 10 genome wide association scans (36,610 individuals of European descent), fasting glucose was most strongly associated with MTNR1B rs10830963 and carriers of the risk allele had increased fasting glucose and increased risk of type 2 diabetes (T2D)( 7 ). The association of MTNR1B rs10830963 with fasting plasma glucose and T2D risk has also been observed in populations of Asian, Mexican and African-American ancestry( 8 – 10 ). Increased fasting glucose is a strong risk factor for the development of T2D( 11 ). It is estimated that 589 million adults, 11.1% of the global population were living with diabetes in 2024; by 2050 it is projected that this will increase by 45% to 853 million adults( 12 ). In the UK, diabetes mellitus is associated with significant cost to both the individual due to increased morbidity and the economy, estimated direct costs in 2021/2022 were £10.7 billion( 13 , 14 ). Consequently, primary prevention approaches to reduce the risk of developing T2D are called for( 13 ). Research suggests the impact of MTNR1B genotype on glucose response is primarily observed when melatonin levels are raised, either through exogenous administration( 5 ) or late evening when endogenous levels are increased( 15 , 16 ). Food consumption also occurs early in the morning when endogenous melatonin levels may be raised. The early morning may be particularly important to investigate since research suggests that MTNR1B rs10830963 G allele carriers have delayed dim-light melatonin offset, meaning that endogenous levels of melatonin remain elevated in the morning for longer than individuals with the CC genotype( 17 ). Additionally, G allele carriers with early sleep timing had an increased T2D risk than those with late sleep timing, in those sleeping later and consequently waking later, breakfast may be eaten once endogenous melatonin levels have decreased( 17 ). Therefore, an individual’s chronotype, the extent to which they are active and alert at different times of the day, may be an important factor to consider( 18 ). Personalised nutrition aims to provide individuals with more effective dietary advice( 19 ). Since the mechanism by which MTNR1B genotype influences glucose response is by impairing insulin secretion, modifying macronutrient composition of breakfast may mitigate some of this effect. Protein, when eaten in combination with carbohydrate, has been reported to increase insulin response compared to carbohydrate alone( 20 , 21 ). Smith et al.( 22 ) reported the enrichment of a carbohydrate breakfast with whey protein significantly reduced the glucose response compared to a carbohydrate-rich breakfast. Consequently, it is important not only to determine the effect of MTNR1B genotype on glucose response but also to be able to provide advice to individuals with the risk associated genotype how they could modify their diet to reduce the associated risk. Therefore, the aim of the present study was to investigate the interaction of MTNR1B rs10830963 genotype and type of breakfast (protein-enriched v carbohydrate-rich) on postprandial glucose response. Methods Participants: Adults (18 to 48 years) living in the UK were recruited to take part in the study between October 2024 and February 2025 (due to the UK sunrise being after 7:00 am). Exclusion criteria applied to those aged less than 18 or more than 48 years (due endogenous melatonin levels significantly lower in older compared to younger adults( 1 ) and the association between MTNR1B rs10830963 is greater younger people( 23 )), had diabetes, a sleep disorder, an eating disorder, an implanted medical device, were taking relevant medication (weight loss, sleeping, melatonin), or following a restricted diet. The study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the St Mary’s University Research Ethics Sub- Committee (SMU_ETHICS_2023-24_626). Written informed consent was obtained from all participants. This study was registered with ClinicalTrials.gov: https://clinicaltrials.gov/study/NCT06821620 . All data were collected and stored according to the Data Protection Act 1998 and the Human Tissue Authority. Experimental design: To recruit an equal number of participants to represent genotype groups the study began with a genotype screening phase. All GG participants were invited to enrol into the main study, participants with CC and CG genotype were enrolled based on matching to the GG group for age, sex and body mass index (BMI) (Fig. 2 ). Baseline: Enrolled participants met with a researcher to measure height and weight, receive instruction on how to record their diet, exercise and sleep, prepare their breakfasts, collect and store their saliva samples, were fitted with a CGM and completed an online chronotype questionnaire. Experimental Condition 1: At least three days later, following an 8h fast, participants woke at 6.30am, avoiding exposure to bright light. At 6.55am participants collected a saliva sample to measure their melatonin level. At 7.00am participants consumed their allocated breakfast and remained at home in dim light, not consuming any food or drinks except water until 9am. Participants were randomly allocated by the lead researcher (AK) using Research Randomizer (Version4.0) to receive a carbohydrate-rich or protein-enriched breakfast( 24 ). Participants were blind to which breakfast they were assigned in each experimental condition, the researcher enrolling participants had access to allocation. Breakfasts were provided in non-transparent packaging. The amount of breakfast (g) for each participant was calculated to deliver 7.3mg carbohydrate / kJ basal metabolic rate (BMR), based on the carbohydrate-rich breakfast condition (sufficient metabolic challenge to assess glucose tolerance( 22 )). The same amount of breakfast (grams and energy) was consumed in the protein-enriched condition (Table 1). Participants were asked to refrain from strenuous exercise and alcohol for 24 hours prior to the breakfast. Experimental Condition 2: One week later, participants followed exactly the same procedure as for Experimental Condition 1, consuming the other breakfast condition. Participants were asked to replicate their dietary intake and exercise prior to Experimental Condition 1 for 24 hours (Fig. 1 ). Measures: Participant characteristics: All participants reported their age, sex, height and weight. For the main study height was measured to the nearest 0.1cm using a Free-Standing Height Measure (seca 217 Stadiometer, seca, Birmingham, UK), weight was measured clothed without shoes or over garments to the nearest 0.1kg, using a portable weighing scale (Argos Home Digital Bathroom scale, Argos Ltd., Milton Keynes, UK). BMI was calculated by dividing participants’ weight (kg) by their height (m) squared. BMR was estimated for each participant based on the Henry( 25 ) equations. Participants were also asked to report their ethnicity. DNA isolation and genotyping: Cheek cells were collected by participants using Isohelix RD-01 Buccal Swabs (Isohelix, Kent, UK). DNA extraction and purification was carried out following manufacturer’s guidelines. DNA quantitation and quality control was carried out using Nanodrop 2000 Series spectrophotometer (ThermoFisher, Waltham, MA, USA). Genotyping for MTNR1B genotype rs10830963 was carried out using the TaqMan® method using qPCR (StepOnePlus RT-PCR system, Applied Biosystems, CA, USA). Call rate for rs10830963 was 97% and genotype frequencies were within Hardy-Weinberg Equilibrium (p = 0.934). Dietary intake, sleep diary and chronotype: For two days prior to each experimental condition and the day of the breakfast participants reported the amount, type and timing of all food and beverages consumed using Libro App( 26 ). For sleep, they recorded the time they went to bed, wake-up time, duration and quality of sleep. Participants reported whether they exercised, the duration (minutes) and intensity (light, moderate, vigorous, high) of the exercise. They also reported how fatigued and how stressed they felt (both rated from 1–7). Participants completed the 19 item morningness/eveningness questionnaire to determine their chronotype( 18 ). Glucose response: Glucose response was measured using a CGM (FreeStyle Libre Pro iQ; Abbott Diabetes Care, Oxon, UK), as used in previous research( 27 ). The sensor measured and stored glucose readings every 15 minutes for 14 days. The 120-minute iAUC was calculated for each participant following each breakfast condition. Participants were blinded to the glucose data for the duration of the study. Melatonin: Melatonin concentration was determined from a salivary melatonin sample, collected by participants immediately prior to each breakfast condition, as used in previous research( 16 ). Samples were stored at -20°C until analysed for salivary melatonin concentration by enzyme-linked immunosorbent assay analysis. Statistical analysis: According to a sample size calculation, to identify a medium effect size (Cohen’s d = 0.4), for a two-tailed test, with a power of 0.8 and probability of 0.05, 22 participants per group were required. The sample size calculation was conducted using the statistical power analyses software G*Power version 3.1.9.2 (Faul et al., 2007). In order to identify 22 participants with the GG genotype, which has a population frequency of 9%, we aimed to recruit 240 participants to the screening phase of the study, with the intention to have 66 participants in the main study, 22 for each genotype in line with previous research( 16 , 22 , 28 ). Statistical analysis was carried out using IBM SPSS Statistics 30 for Windows (IBM Corp, New York, USA). Measures of centrality and spread are presented as means ± SD; categorical data are presented as frequencies and percentages. Normality of data was assessed using the Shapiro-Wilk test. Continuous measures were compared between genotype groups using a one-way ANOVA for normally distributed data or an Independent-Samples Kruskal-Wallis test for data that was not normally distributed. A two-way mixed ANOVA was used to determine the effect of genotype (CC, CG, GG) and breakfast (carbohydrate-rich v protein-enriched) on glucose response (iAUC). All tests were two-tailed and considered statistically significant when p < 0.05. Results For the screening phase, 247 participants were genotyped for MTNR1B rs10830963 (CC = 119, 48%, CG = 107, 43%, GG = 21, 9%). Main study participant characteristics: Genotype groups did not differ significantly in age (F = 0.041, p = 0.960), sex (χ 2 = 0.008, p = 0.996), ethnicity (χ 2 = 3.179, p = 0.923), height (F = 0.816, p = 0.448), weight (F = 0.425, p = 0.656) or BMI (F = 0.025, p = 0.975). Participants with a GG genotype had a significantly higher chronotype score than participants with a CC or CG genotype (F = 3.385, p = 0.042). Fasting glucose was significantly higher in the GG genotype group compared to the CC or CG group (F = 5.28, p = 0.008) (Table 2). Breakfast type and glucose response: There was a significantly greater iAUC for glucose following the carbohydrate-rich breakfast compared to the protein-enriched breakfast, irrespective of participants genotype (F = 24.161, p < 0.001; Fig. 3 ). Breakfast type and genotype interaction on glucose response: Following the carbohydrate-rich breakfast, participants with a GG genotype had a significantly greater iAUC for glucose than participants with a CC (p = 0.026) or CG (p = 0.029) genotype. There was no significant difference in iAUC for glucose between the CC and CG group (p = 0.943, Fig. 4 ). However, following the protein-enriched breakfast there was no significant difference in iAUC for glucose between the GG genotype group and the CC (p = 0.904) or CG (p = 0.958) groups. There was no significant difference between the CC and CG group (p = 0.853, Fig. 5 ). There was no significant difference in salivary melatonin levels between genotype groups in the carbohydrate-rich (H = 4.464, p = 0.107) or the protein-enriched breakfast condition (H = 0.862, p = 0.650, Table 2). Discussion The aim of the present study was to investigate the interaction between MTNR1B genotype and type of breakfast (protein-enriched v carbohydrate-rich) on postprandial glucose response. The primary findings of this study suggest that GG genotype for MTNR1B is associated with an impaired glucose response following a carbohydrate-rich breakfast compared to a CC or CG genotype. However, following a protein-enriched breakfast there was no significant difference in post-prandial glucose response between MTNR1B genotype groups. The findings are in line with those of Lopez-Minguez et al.( 16 ) (20 = CC, 20 = GG) and Garaulet et al.( 15 ) (80 = GG, 342 = GC, 423 = CC) who also investigated the effect of late-evening endogenous melatonin levels and MTNR1B genotype on glucose response. In both studies glucose response in all participants was significantly greater in the late compared to early-evening condition. However, when analysed by genotype the difference was significantly greater in the GG group( 15 , 16 ) followed by the CG group( 15 ). Furthermore, insulin iAUC was significantly decreased in G allele carriers in the late compared to early-evening condition in line with the proposed gain of function of MT2 receptors in G allele carriers( 15 ). Whilst these studies suggest that eating late in the evening is associated with impaired post-prandial glucose response in individuals with the GG genotype, our findings confirm that this is also the case for GG participants eating early before endogenous melatonin levels have decreased. Mean salivary melatonin levels at the start of the experimental conditions were 25.1 ± 18.3pg/ml in the carbohydrate-rich and 24.1 ± 17.6pg/ml in the protein-enriched condition. These are both well above the reported endogenous daytime melatonin levels of < 5pg/ml, confirming that at the time participants in the present study consumed their breakfast melatonin levels were still raised( 1 ). Previous research had suggested that there is a delayed dim light offset of melatonin in individuals with MTNR1B GG genotype( 17 ). However, melatonin levels were not significantly different between MTNR1B genotype groups in the present study. Despite this the raised melatonin levels in all groups confirm that breakfast is an important eating episode to consider in terms of personalised advice to those with the risk MTNR1B genotype. As in previous studies( 7 – 10 ), MTNR1B GG genotype was associated with a significantly higher fasting blood glucose. Previous research has suggested that MTNR1B risk genotype may increase the risk of progressing from normal glucose tolerance to impaired fasting glucose( 29 ). A fasting glucose level greater than 5.5 mmol/L is associated with a high risk of developing T2D( 11 ). In the present study the mean fasting glucose for GG participants (5.53 ± 0.43mmol/L) suggests they are at increased risk of developing T2D compared to CC (5.02 ± 0.42mmol/L) and CG groups (5.19 ± 0.52mmol/L), despite having on average the same age, sex and BMI. In the UK, adults who are identified to have a high risk of developing T2D are offered generic advice to increase their physical activity and improve their diet( 11 ). However, based on our findings and those of previous studies( 15 – 17 ), participants may benefit from more personalised advice based on their MTNR1B genotype. To facilitate the delivery of personalised advice, we investigated the effect of modifying the macronutrient composition of participants’ breakfasts on their glucose response. In line with previous research we found that enrichment of a high-carbohydrate breakfast with protein reduced the subsequent glucose response( 22 ). Importantly, the enrichment of the breakfast with protein mitigated the effect of MTNR1B genotype on glucose response. Therefore, individuals with MTNR1B GG genotype should be advised against eating early and if they do, to eat a protein-enriched rather than carbohydrate-rich breakfast. The addition of protein to a carbohydrate meal increases the insulin response to that meal, which can compensate for the reduced insulin response and increased glucose response observed in individuals with a GG MTNR1B genotype( 15 , 20 – 22 ). In the present study the MTNR1B GG group had a significantly higher chronotype score than the CC or CG groups. A higher chronotype score reflects a more ‘morning-type’, on average the GG group were classified as being ‘moderately morning type’ whereas the CC and CG groups were both classified as ‘neither type’( 18 ). This finding may have increased importance due to the findings of Lane et al.( 17 ), that those with early sleep timing had an increased risk of T2D compared to those with late sleep timing. Individuals with a morning chronotype are more likely to sleep earlier, wake earlier and consequently eat their breakfast earlier when melatonin levels are raised, making advice around breakfast timing and composition even more pertinent to this group. Strengths of the present study include the real world setting in which it was conducted, participants consumed a realistic breakfast meal rather than an OGTT( 30 ). The use of CGM as opposed to blood sampling facilitated a reduced burden for the participants in order to collect data from early in the morning. Inclusion of all three genotype groups, rather than grouping GG with CG genotypes strengthened the design of the study although made it more difficult to meet our sample size. This is the main limitation of the study; we did not meet the a priori sample size of 22 participants for each group. However, despite having a smaller number of participants particularly in the GG group we still observed statistically significant differences in both fasting glucose and post-prandial glucose iAUC. In the larger study by Garulet et al.( 15 ) significant differences were also observed in glucose response to an OGTT between CG and CC genotypes, if we had a larger sample size this difference may also become apparent in a breakfast study. Whilst prevalence of the GG MTNR1B genotype is relatively low (9%) in a European population, if findings and consequently advice was extended to those with a CG genotype this would reflect over 50% of the population. The majority (80%) of the participants in the present study were female, which may limit the generalisability of the findings. Finally, insulin was not measured in the present study so we can only hypothesise based on previous work that reduced insulin secretion in MTNR1B GG participants was the mechanism for increased glucose response in the carbohydrate-rich breakfast condition and enhanced insulin secretion in the protein-enriched breakfast condition reduced glucose response( 20 – 22 ). In conclusion, the present study found that MTNR1B GG genotype is associated with an impaired glucose response following a carbohydrate-rich breakfast. However, if the carbohydrate breakfast is enriched with protein, the effect of genotype on glucose response was not observed. The study also confirmed previous findings that the MTNR1B GG genotype is associated with increased fasting glucose levels in a relatively healthy and young adult population, which may place an individual at high risk of developing T2D. Therefore, personalised advice to individuals based on their MTNR1B genotype may reduce their risk of developing T2D. Declarations Ethical Approval: Ethical approval was obtained from the St Mary’s University Research Ethics Sub- Committee (SMU_ETHICS_2023-24_626). Written informed consent was obtained from all participants. Competing Interests: YM reports a relationship with MyHealthChecked that includes: consulting or advisory and Nudge Care that includes: equity or stocks. LP reports a relationship with Optimyse Nutrition that includes: equity or stocks. AKap reports a relationship with iDNA Laboratories S. A., Private Diagnostic Laboratories that includes: employment. Funding: St Mary’s University provided funding for the study. Author Contributions: All authors conceived and designed the work that led to the submission. AK, JN and JC acquired data. AK, JN and AKap played an important role in interpreting the results. AK drafted and all authors revised the manuscript. 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Available from: https://www.ensembl.org/Homo_sapiens/Variation/Population?db=core;r=11 :92975044-92976044;v=rs10830963;vdb=variation;vf=706707438 Walford GA, Green T, Neale B, Isakova T, Rotter JI, Grant SFA, et al. Common genetic variants differentially influence the transition from clinically defined states of fasting glucose metabolism. Diabetologia. 2012;55(2):331–9. Chodankar D. Introduction to real-world evidence studies. Perspect Clin Res. 2021;12(3):171–4. Tables Table 1 and 2 are available in the Supplementary Files section. Additional Declarations Yes there is potential conflict of interest. Supplementary Files Table1.Nutritionalcompositionofcarbohydraterichandproteinenrichedbreakfastsper100g.xlsx Table 1 Table2.Participantcharacteristicsn54presentedasfrequencypercentageormeanXXstandarddeviation.xlsx Table 2 Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: revise 07 Apr, 2026 Review # 2 received at journal 02 Apr, 2026 Review # 1 received at journal 31 Mar, 2026 Reviewer # 2 agreed at journal 18 Mar, 2026 Reviewer # 1 agreed at journal 09 Mar, 2026 Reviewers invited by journal 09 Feb, 2026 Editor assigned by journal 01 Feb, 2026 Submission checks completed at journal 01 Feb, 2026 First submitted to journal 29 Jan, 2026 Unknown event 28 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8678875","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":588618091,"identity":"ac56a9eb-2cc6-494f-9278-c9656ba61afb","order_by":0,"name":"Alexandra King","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-1788-5402","institution":"St Marys University","correspondingAuthor":true,"prefix":"","firstName":"Alexandra","middleName":"","lastName":"King","suffix":""},{"id":588618092,"identity":"842ed022-6ebe-46d4-8c92-158620fc5a2f","order_by":1,"name":"Yiannis Mavrommatis","email":"","orcid":"https://orcid.org/0000-0003-2717-6324","institution":"Lake Lucerne Institute (LLUI)","correspondingAuthor":false,"prefix":"","firstName":"Yiannis","middleName":"","lastName":"Mavrommatis","suffix":""},{"id":588618093,"identity":"307f87b6-8dce-4e42-8095-fe6e4e2ea98b","order_by":2,"name":"Jonathan Nixon","email":"","orcid":"","institution":"St Marys University","correspondingAuthor":false,"prefix":"","firstName":"Jonathan","middleName":"","lastName":"Nixon","suffix":""},{"id":588618094,"identity":"09fee9b3-4884-41cb-a951-c6923a4128fe","order_by":3,"name":"Angeliki Kapellou","email":"","orcid":"https://orcid.org/0000-0003-4545-2257","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Angeliki","middleName":"","lastName":"Kapellou","suffix":""},{"id":588618095,"identity":"baaa084b-fa3c-42f3-b0f4-9bb442383de9","order_by":4,"name":"Jonathan Craven","email":"","orcid":"","institution":"St Marys University","correspondingAuthor":false,"prefix":"","firstName":"Jonathan","middleName":"","lastName":"Craven","suffix":""},{"id":588618096,"identity":"8593409c-451d-4d0a-a011-bae0ce21da81","order_by":5,"name":"Catherine Graham","email":"","orcid":"","institution":"Lake Lucerne Institute (LLUI)","correspondingAuthor":false,"prefix":"","firstName":"Catherine","middleName":"","lastName":"Graham","suffix":""},{"id":588618097,"identity":"01917e5c-43f8-43c4-a27d-2aa6f2a64b8c","order_by":6,"name":"Leta Pilic","email":"","orcid":"","institution":"Optimyse Nutrition LTD","correspondingAuthor":false,"prefix":"","firstName":"Leta","middleName":"","lastName":"Pilic","suffix":""}],"badges":[],"createdAt":"2026-01-23 11:45:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8678875/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8678875/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102598068,"identity":"ea740b8c-f893-4c74-a0a5-54ef50f02dac","added_by":"auto","created_at":"2026-02-13 12:27:13","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":413160,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic of experimental protocol.\u003c/p\u003e","description":"","filename":"F1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8678875/v1/49020eae4f0a5c4708de9744.jpg"},{"id":102598070,"identity":"741141ee-653e-445e-8ce5-9d25ea99e607","added_by":"auto","created_at":"2026-02-13 12:27:13","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":397664,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flow chart.\u003c/p\u003e","description":"","filename":"F2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8678875/v1/43fe825ae9523e5382552933.jpg"},{"id":102598060,"identity":"566dab46-cf76-4566-93b5-6280fec33194","added_by":"auto","created_at":"2026-02-13 12:27:11","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":87773,"visible":true,"origin":"","legend":"\u003cp\u003eGlucose response following carbohydrate-rich and protein-enriched breakfast in all participants (n = 54), iAUC significantly greater in carbohydrate-rich breakfast condition (p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"F3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8678875/v1/1bb5bd9fcbe606607f4a588f.jpg"},{"id":102598064,"identity":"e7c17726-25de-4422-b460-1105a631c58c","added_by":"auto","created_at":"2026-02-13 12:27:12","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":89178,"visible":true,"origin":"","legend":"\u003cp\u003eGlucose response following carbohydrate-rich breakfast in participants by \u003cem\u003eMTNR1B\u003c/em\u003egenotype, iAUC significantly greater in GG compared to CC (p = 0.026) and CG (p = 0.029).\u003c/p\u003e","description":"","filename":"F4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8678875/v1/b9ce01770b9304a6601e7a17.jpg"},{"id":102598040,"identity":"a94bc920-f10f-4d54-9c29-738b347a2d81","added_by":"auto","created_at":"2026-02-13 12:27:08","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":82005,"visible":true,"origin":"","legend":"\u003cp\u003eGlucose response to protein-enriched breakfast in participants by \u003cem\u003eMTNR1B\u003c/em\u003e genotype. No significant difference in iAUC between genotype groups.\u003c/p\u003e","description":"","filename":"F5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8678875/v1/278e567aa153addbb2276f8b.jpg"},{"id":102598108,"identity":"c31d5cc1-f58f-4ff9-ae41-09fb6a4a2bc3","added_by":"auto","created_at":"2026-02-13 12:27:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1754839,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8678875/v1/82939d15-2e66-4b08-a16e-ba2c90eb4b9e.pdf"},{"id":102598013,"identity":"84136689-7402-48c2-b88a-94a9af7097f2","added_by":"auto","created_at":"2026-02-13 12:27:01","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20744,"visible":true,"origin":"","legend":"Table 1","description":"","filename":"Table1.Nutritionalcompositionofcarbohydraterichandproteinenrichedbreakfastsper100g.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8678875/v1/77132bc03e94a780a0746b42.xlsx"},{"id":102598010,"identity":"0b9d998e-3d6e-4735-a10f-44345e588e6b","added_by":"auto","created_at":"2026-02-13 12:27:00","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":21016,"visible":true,"origin":"","legend":"Table 2","description":"","filename":"Table2.Participantcharacteristicsn54presentedasfrequencypercentageormeanXXstandarddeviation.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8678875/v1/53412704272a9adbd7dcb282.xlsx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential conflict of interest.","formattedTitle":"Interaction of melatonin receptor 1B (MTNR1B) genotype and type of breakfast (protein-enriched v carbohydrate-rich) on postprandial glucose response: a randomised crossover trial.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMelatonin is a circadian hormone, synthesis and release of melatonin are inhibited by daytime light. Consequently, levels of melatonin fluctuate over the 24h day, increasing during the evening, peaking in the early hours of the morning and then reducing(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In addition to sleep quality and circadian regulation, melatonin is linked to glucose metabolism. Melatonin mediates insulin secretion in pancreatic β-cells via the G protein-coupled melatonin receptors (MT1 and MT2). Binding of melatonin to MT1 and MT2 inhibits cyclic adenosine monophosphate and cyclic guanine monophosphate signalling causing decreased insulin secretion(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Furthermore, studies have demonstrated that administration of exogenous melatonin (1-5mg) prior to an oral glucose tolerance test (OGTT) results in a significantly greater glucose response(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe \u003cem\u003emelatonin receptor 1B\u003c/em\u003e (\u003cem\u003eMTNR1B\u003c/em\u003e) gene codes for the MT2 receptor and is expressed in a number of tissues including the pancreas(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). A variation in the \u003cem\u003eMTNR1B\u003c/em\u003e gene rs10830963 is associated with increased expression of MT2 in islet cells of people with the risk (G) allele(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In an analysis of 10 genome wide association scans (36,610 individuals of European descent), fasting glucose was most strongly associated with \u003cem\u003eMTNR1B\u003c/em\u003e rs10830963 and carriers of the risk allele had increased fasting glucose and increased risk of type 2 diabetes (T2D)(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The association of \u003cem\u003eMTNR1B\u003c/em\u003e rs10830963 with fasting plasma glucose and T2D risk has also been observed in populations of Asian, Mexican and African-American ancestry(\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIncreased fasting glucose is a strong risk factor for the development of T2D(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). It is estimated that 589\u0026nbsp;million adults, 11.1% of the global population were living with diabetes in 2024; by 2050 it is projected that this will increase by 45% to 853\u0026nbsp;million adults(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In the UK, diabetes mellitus is associated with significant cost to both the individual due to increased morbidity and the economy, estimated direct costs in 2021/2022 were \u0026pound;10.7\u0026nbsp;billion(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Consequently, primary prevention approaches to reduce the risk of developing T2D are called for(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResearch suggests the impact of \u003cem\u003eMTNR1B\u003c/em\u003e genotype on glucose response is primarily observed when melatonin levels are raised, either through exogenous administration(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) or late evening when endogenous levels are increased(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Food consumption also occurs early in the morning when endogenous melatonin levels may be raised. The early morning may be particularly important to investigate since research suggests that \u003cem\u003eMTNR1B\u003c/em\u003e rs10830963 G allele carriers have delayed dim-light melatonin offset, meaning that endogenous levels of melatonin remain elevated in the morning for longer than individuals with the CC genotype(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Additionally, G allele carriers with early sleep timing had an increased T2D risk than those with late sleep timing, in those sleeping later and consequently waking later, breakfast may be eaten once endogenous melatonin levels have decreased(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Therefore, an individual\u0026rsquo;s chronotype, the extent to which they are active and alert at different times of the day, may be an important factor to consider(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePersonalised nutrition aims to provide individuals with more effective dietary advice(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Since the mechanism by which \u003cem\u003eMTNR1B\u003c/em\u003e genotype influences glucose response is by impairing insulin secretion, modifying macronutrient composition of breakfast may mitigate some of this effect. Protein, when eaten in combination with carbohydrate, has been reported to increase insulin response compared to carbohydrate alone(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Smith et al.(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) reported the enrichment of a carbohydrate breakfast with whey protein significantly reduced the glucose response compared to a carbohydrate-rich breakfast. Consequently, it is important not only to determine the effect of \u003cem\u003eMTNR1B\u003c/em\u003e genotype on glucose response but also to be able to provide advice to individuals with the risk associated genotype how they could modify their diet to reduce the associated risk. Therefore, the aim of the present study was to investigate the interaction of \u003cem\u003eMTNR1B\u003c/em\u003e rs10830963 genotype and type of breakfast (protein-enriched v carbohydrate-rich) on postprandial glucose response.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants:\u003c/h2\u003e \u003cp\u003eAdults (18 to 48 years) living in the UK were recruited to take part in the study between October 2024 and February 2025 (due to the UK sunrise being after 7:00 am). Exclusion criteria applied to those aged less than 18 or more than 48 years (due endogenous melatonin levels significantly lower in older compared to younger adults(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) and the association between \u003cem\u003eMTNR1B\u003c/em\u003e rs10830963 is greater younger people(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)), had diabetes, a sleep disorder, an eating disorder, an implanted medical device, were taking relevant medication (weight loss, sleeping, melatonin), or following a restricted diet. The study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the St Mary\u0026rsquo;s University Research Ethics Sub- Committee (SMU_ETHICS_2023-24_626). Written informed consent was obtained from all participants. This study was registered with ClinicalTrials.gov: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://clinicaltrials.gov/study/NCT06821620\u003c/span\u003e\u003cspan address=\"https://clinicaltrials.gov/study/NCT06821620\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. All data were collected and stored according to the Data Protection Act 1998 and the Human Tissue Authority.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperimental design:\u003c/h3\u003e\n\u003cp\u003e To recruit an equal number of participants to represent genotype groups the study began with a genotype screening phase. All GG participants were invited to enrol into the main study, participants with CC and CG genotype were enrolled based on matching to the GG group for age, sex and body mass index (BMI) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eBaseline:\u003c/h3\u003e\n\u003cp\u003eEnrolled participants met with a researcher to measure height and weight, receive instruction on how to record their diet, exercise and sleep, prepare their breakfasts, collect and store their saliva samples, were fitted with a CGM and completed an online chronotype questionnaire.\u003c/p\u003e\n\u003ch3\u003eExperimental Condition 1:\u003c/h3\u003e\n\u003cp\u003eAt least three days later, following an 8h fast, participants woke at 6.30am, avoiding exposure to bright light. At 6.55am participants collected a saliva sample to measure their melatonin level. At 7.00am participants consumed their allocated breakfast and remained at home in dim light, not consuming any food or drinks except water until 9am. Participants were randomly allocated by the lead researcher (AK) using Research Randomizer (Version4.0) to receive a carbohydrate-rich or protein-enriched breakfast(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Participants were blind to which breakfast they were assigned in each experimental condition, the researcher enrolling participants had access to allocation. Breakfasts were provided in non-transparent packaging. The amount of breakfast (g) for each participant was calculated to deliver 7.3mg carbohydrate / kJ basal metabolic rate (BMR), based on the carbohydrate-rich breakfast condition (sufficient metabolic challenge to assess glucose tolerance(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)). The same amount of breakfast (grams and energy) was consumed in the protein-enriched condition (Table\u0026nbsp;1). Participants were asked to refrain from strenuous exercise and alcohol for 24 hours prior to the breakfast.\u003c/p\u003e\n\u003ch3\u003eExperimental Condition 2:\u003c/h3\u003e\n\u003cp\u003eOne week later, participants followed exactly the same procedure as for Experimental Condition 1, consuming the other breakfast condition. Participants were asked to replicate their dietary intake and exercise prior to Experimental Condition 1 for 24 hours (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMeasures:\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eParticipant characteristics:\u003c/h2\u003e \u003cp\u003eAll participants reported their age, sex, height and weight. For the main study height was measured to the nearest 0.1cm using a Free-Standing Height Measure (seca 217 Stadiometer, seca, Birmingham, UK), weight was measured clothed without shoes or over garments to the nearest 0.1kg, using a portable weighing scale (Argos Home Digital Bathroom scale, Argos Ltd., Milton Keynes, UK). BMI was calculated by dividing participants\u0026rsquo; weight (kg) by their height (m) squared. BMR was estimated for each participant based on the Henry(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) equations. Participants were also asked to report their ethnicity.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eDNA isolation and genotyping:\u003c/h3\u003e\n\u003cp\u003eCheek cells were collected by participants using Isohelix RD-01 Buccal Swabs (Isohelix, Kent, UK). DNA extraction and purification was carried out following manufacturer\u0026rsquo;s guidelines. DNA quantitation and quality control was carried out using Nanodrop 2000 Series spectrophotometer (ThermoFisher, Waltham, MA, USA). Genotyping for \u003cem\u003eMTNR1B\u003c/em\u003e genotype rs10830963 was carried out using the TaqMan\u0026reg; method using qPCR (StepOnePlus RT-PCR system, Applied Biosystems, CA, USA). Call rate for rs10830963 was 97% and genotype frequencies were within Hardy-Weinberg Equilibrium (p\u0026thinsp;=\u0026thinsp;0.934).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDietary intake, sleep diary and chronotype:\u003c/h2\u003e \u003cp\u003eFor two days prior to each experimental condition and the day of the breakfast participants reported the amount, type and timing of all food and beverages consumed using Libro App(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). For sleep, they recorded the time they went to bed, wake-up time, duration and quality of sleep. Participants reported whether they exercised, the duration (minutes) and intensity (light, moderate, vigorous, high) of the exercise. They also reported how fatigued and how stressed they felt (both rated from 1\u0026ndash;7). Participants completed the 19 item morningness/eveningness questionnaire to determine their chronotype(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eGlucose response:\u003c/h2\u003e \u003cp\u003eGlucose response was measured using a CGM (FreeStyle Libre Pro iQ; Abbott Diabetes Care, Oxon, UK), as used in previous research(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). The sensor measured and stored glucose readings every 15 minutes for 14 days. The 120-minute iAUC was calculated for each participant following each breakfast condition. Participants were blinded to the glucose data for the duration of the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMelatonin:\u003c/h2\u003e \u003cp\u003eMelatonin concentration was determined from a salivary melatonin sample, collected by participants immediately prior to each breakfast condition, as used in previous research(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Samples were stored at -20\u0026deg;C until analysed for salivary melatonin concentration by enzyme-linked immunosorbent assay analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003eAccording to a sample size calculation, to identify a medium effect size (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.4), for a two-tailed test, with a power of 0.8 and probability of 0.05, 22 participants per group were required. The sample size calculation was conducted using the statistical power analyses software G*Power version 3.1.9.2 (Faul et al., 2007). In order to identify 22 participants with the GG genotype, which has a population frequency of 9%, we aimed to recruit 240 participants to the screening phase of the study, with the intention to have 66 participants in the main study, 22 for each genotype in line with previous research(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Statistical analysis was carried out using IBM SPSS Statistics 30 for Windows (IBM Corp, New York, USA). Measures of centrality and spread are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; categorical data are presented as frequencies and percentages. Normality of data was assessed using the Shapiro-Wilk test. Continuous measures were compared between genotype groups using a one-way ANOVA for normally distributed data or an Independent-Samples Kruskal-Wallis test for data that was not normally distributed. A two-way mixed ANOVA was used to determine the effect of genotype (CC, CG, GG) and breakfast (carbohydrate-rich v protein-enriched) on glucose response (iAUC). All tests were two-tailed and considered statistically significant when p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFor the screening phase, 247 participants were genotyped for \u003cem\u003eMTNR1B\u003c/em\u003e rs10830963 (CC\u0026thinsp;=\u0026thinsp;119, 48%, CG\u0026thinsp;=\u0026thinsp;107, 43%, GG\u0026thinsp;=\u0026thinsp;21, 9%).\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMain study participant characteristics:\u003c/h2\u003e \u003cp\u003eGenotype groups did not differ significantly in age (F\u0026thinsp;=\u0026thinsp;0.041, p\u0026thinsp;=\u0026thinsp;0.960), sex (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.008, p\u0026thinsp;=\u0026thinsp;0.996), ethnicity (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;3.179, p\u0026thinsp;=\u0026thinsp;0.923), height (F\u0026thinsp;=\u0026thinsp;0.816, p\u0026thinsp;=\u0026thinsp;0.448), weight (F\u0026thinsp;=\u0026thinsp;0.425, p\u0026thinsp;=\u0026thinsp;0.656) or BMI (F\u0026thinsp;=\u0026thinsp;0.025, p\u0026thinsp;=\u0026thinsp;0.975). Participants with a GG genotype had a significantly higher chronotype score than participants with a CC or CG genotype (F\u0026thinsp;=\u0026thinsp;3.385, p\u0026thinsp;=\u0026thinsp;0.042). Fasting glucose was significantly higher in the GG genotype group compared to the CC or CG group (F\u0026thinsp;=\u0026thinsp;5.28, p\u0026thinsp;=\u0026thinsp;0.008) (Table\u0026nbsp;2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eBreakfast type and glucose response:\u003c/h2\u003e \u003cp\u003eThere was a significantly greater iAUC for glucose following the carbohydrate-rich breakfast compared to the protein-enriched breakfast, irrespective of participants genotype (F\u0026thinsp;=\u0026thinsp;24.161, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eBreakfast type and genotype interaction on glucose response:\u003c/h2\u003e \u003cp\u003eFollowing the carbohydrate-rich breakfast, participants with a GG genotype had a significantly greater iAUC for glucose than participants with a CC (p\u0026thinsp;=\u0026thinsp;0.026) or CG (p\u0026thinsp;=\u0026thinsp;0.029) genotype. There was no significant difference in iAUC for glucose between the CC and CG group (p\u0026thinsp;=\u0026thinsp;0.943, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). However, following the protein-enriched breakfast there was no significant difference in iAUC for glucose between the GG genotype group and the CC (p\u0026thinsp;=\u0026thinsp;0.904) or CG (p\u0026thinsp;=\u0026thinsp;0.958) groups. There was no significant difference between the CC and CG group (p\u0026thinsp;=\u0026thinsp;0.853, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e). There was no significant difference in salivary melatonin levels between genotype groups in the carbohydrate-rich (H\u0026thinsp;=\u0026thinsp;4.464, p\u0026thinsp;=\u0026thinsp;0.107) or the protein-enriched breakfast condition (H\u0026thinsp;=\u0026thinsp;0.862, p\u0026thinsp;=\u0026thinsp;0.650, Table\u0026nbsp;2).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe aim of the present study was to investigate the interaction between \u003cem\u003eMTNR1B\u003c/em\u003e genotype and type of breakfast (protein-enriched v carbohydrate-rich) on postprandial glucose response. The primary findings of this study suggest that GG genotype for \u003cem\u003eMTNR1B\u003c/em\u003e is associated with an impaired glucose response following a carbohydrate-rich breakfast compared to a CC or CG genotype. However, following a protein-enriched breakfast there was no significant difference in post-prandial glucose response between \u003cem\u003eMTNR1B\u003c/em\u003e genotype groups. The findings are in line with those of Lopez-Minguez et al.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) (20\u0026thinsp;=\u0026thinsp;CC, 20\u0026thinsp;=\u0026thinsp;GG) and Garaulet et al.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) (80\u0026thinsp;=\u0026thinsp;GG, 342\u0026thinsp;=\u0026thinsp;GC, 423\u0026thinsp;=\u0026thinsp;CC) who also investigated the effect of late-evening endogenous melatonin levels and \u003cem\u003eMTNR1B\u003c/em\u003e genotype on glucose response. In both studies glucose response in all participants was significantly greater in the late compared to early-evening condition. However, when analysed by genotype the difference was significantly greater in the GG group(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) followed by the CG group(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Furthermore, insulin iAUC was significantly decreased in G allele carriers in the late compared to early-evening condition in line with the proposed gain of function of MT2 receptors in G allele carriers(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Whilst these studies suggest that eating late in the evening is associated with impaired post-prandial glucose response in individuals with the GG genotype, our findings confirm that this is also the case for GG participants eating early before endogenous melatonin levels have decreased.\u003c/p\u003e \u003cp\u003eMean salivary melatonin levels at the start of the experimental conditions were 25.1\u0026thinsp;\u0026plusmn;\u0026thinsp;18.3pg/ml in the carbohydrate-rich and 24.1\u0026thinsp;\u0026plusmn;\u0026thinsp;17.6pg/ml in the protein-enriched condition. These are both well above the reported endogenous daytime melatonin levels of \u0026lt;\u0026thinsp;5pg/ml, confirming that at the time participants in the present study consumed their breakfast melatonin levels were still raised(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Previous research had suggested that there is a delayed dim light offset of melatonin in individuals with \u003cem\u003eMTNR1B\u003c/em\u003e GG genotype(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). However, melatonin levels were not significantly different between \u003cem\u003eMTNR1B\u003c/em\u003e genotype groups in the present study. Despite this the raised melatonin levels in all groups confirm that breakfast is an important eating episode to consider in terms of personalised advice to those with the risk \u003cem\u003eMTNR1B\u003c/em\u003e genotype.\u003c/p\u003e \u003cp\u003eAs in previous studies(\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), \u003cem\u003eMTNR1B\u003c/em\u003e GG genotype was associated with a significantly higher fasting blood glucose. Previous research has suggested that \u003cem\u003eMTNR1B\u003c/em\u003e risk genotype may increase the risk of progressing from normal glucose tolerance to impaired fasting glucose(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). A fasting glucose level greater than 5.5 mmol/L is associated with a high risk of developing T2D(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). In the present study the mean fasting glucose for GG participants (5.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43mmol/L) suggests they are at increased risk of developing T2D compared to CC (5.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42mmol/L) and CG groups (5.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52mmol/L), despite having on average the same age, sex and BMI. In the UK, adults who are identified to have a high risk of developing T2D are offered generic advice to increase their physical activity and improve their diet(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). However, based on our findings and those of previous studies(\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), participants may benefit from more personalised advice based on their \u003cem\u003eMTNR1B\u003c/em\u003e genotype.\u003c/p\u003e \u003cp\u003eTo facilitate the delivery of personalised advice, we investigated the effect of modifying the macronutrient composition of participants\u0026rsquo; breakfasts on their glucose response. In line with previous research we found that enrichment of a high-carbohydrate breakfast with protein reduced the subsequent glucose response(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Importantly, the enrichment of the breakfast with protein mitigated the effect of \u003cem\u003eMTNR1B\u003c/em\u003e genotype on glucose response. Therefore, individuals with \u003cem\u003eMTNR1B\u003c/em\u003e GG genotype should be advised against eating early and if they do, to eat a protein-enriched rather than carbohydrate-rich breakfast. The addition of protein to a carbohydrate meal increases the insulin response to that meal, which can compensate for the reduced insulin response and increased glucose response observed in individuals with a GG \u003cem\u003eMTNR1B\u003c/em\u003e genotype(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In the present study the \u003cem\u003eMTNR1B\u003c/em\u003e GG group had a significantly higher chronotype score than the CC or CG groups. A higher chronotype score reflects a more \u0026lsquo;morning-type\u0026rsquo;, on average the GG group were classified as being \u0026lsquo;moderately morning type\u0026rsquo; whereas the CC and CG groups were both classified as \u0026lsquo;neither type\u0026rsquo;(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). This finding may have increased importance due to the findings of Lane et al.(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), that those with early sleep timing had an increased risk of T2D compared to those with late sleep timing. Individuals with a morning chronotype are more likely to sleep earlier, wake earlier and consequently eat their breakfast earlier when melatonin levels are raised, making advice around breakfast timing and composition even more pertinent to this group.\u003c/p\u003e \u003cp\u003eStrengths of the present study include the real world setting in which it was conducted, participants consumed a realistic breakfast meal rather than an OGTT(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The use of CGM as opposed to blood sampling facilitated a reduced burden for the participants in order to collect data from early in the morning. Inclusion of all three genotype groups, rather than grouping GG with CG genotypes strengthened the design of the study although made it more difficult to meet our sample size. This is the main limitation of the study; we did not meet the \u003cem\u003ea priori\u003c/em\u003e sample size of 22 participants for each group. However, despite having a smaller number of participants particularly in the GG group we still observed statistically significant differences in both fasting glucose and post-prandial glucose iAUC. In the larger study by Garulet et al.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) significant differences were also observed in glucose response to an OGTT between CG and CC genotypes, if we had a larger sample size this difference may also become apparent in a breakfast study. Whilst prevalence of the GG \u003cem\u003eMTNR1B\u003c/em\u003e genotype is relatively low (9%) in a European population, if findings and consequently advice was extended to those with a CG genotype this would reflect over 50% of the population. The majority (80%) of the participants in the present study were female, which may limit the generalisability of the findings. Finally, insulin was not measured in the present study so we can only hypothesise based on previous work that reduced insulin secretion in \u003cem\u003eMTNR1B\u003c/em\u003e GG participants was the mechanism for increased glucose response in the carbohydrate-rich breakfast condition and enhanced insulin secretion in the protein-enriched breakfast condition reduced glucose response(\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, the present study found that \u003cem\u003eMTNR1B\u003c/em\u003e GG genotype is associated with an impaired glucose response following a carbohydrate-rich breakfast. However, if the carbohydrate breakfast is enriched with protein, the effect of genotype on glucose response was not observed. The study also confirmed previous findings that the \u003cem\u003eMTNR1B\u003c/em\u003e GG genotype is associated with increased fasting glucose levels in a relatively healthy and young adult population, which may place an individual at high risk of developing T2D. Therefore, personalised advice to individuals based on their \u003cem\u003eMTNR1B\u003c/em\u003e genotype may reduce their risk of developing T2D.\u003c/p\u003e"},{"header":"Declarations","content":" \u003ch2\u003eEthical Approval:\u003c/h2\u003e \u003cp\u003eEthical approval was obtained from the St Mary\u0026rsquo;s University Research Ethics Sub- Committee (SMU_ETHICS_2023-24_626). Written informed consent was obtained from all participants.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting Interests:\u003c/strong\u003e \u003cp\u003eYM reports a relationship with MyHealthChecked that includes: consulting or advisory and Nudge Care that includes: equity or stocks. LP reports a relationship with Optimyse Nutrition that includes: equity or stocks. AKap reports a relationship with iDNA Laboratories S. A., Private Diagnostic Laboratories that includes: employment.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003e St Mary\u0026rsquo;s University provided funding for the study.\u003c/p\u003e\u003ch2\u003eAuthor Contributions:\u003c/h2\u003e \u003cp\u003eAll authors conceived and designed the work that led to the submission. AK, JN and JC acquired data. AK, JN and AKap played an important role in interpreting the results. AK drafted and all authors revised the manuscript. All authors approved the final version.\u003c/p\u003e\u003ch2\u003eData Availability Statement:\u003c/h2\u003e \u003cp\u003eadditional data are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhdanova IV, Wurtman RJ, Balcioglu A, Kartashov AI, Lynch HJ. Endogenous Melatonin Levels and the Fate of Exogenous Melatonin: Age Effects. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences. 1998 July 1;53A(4):B293\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu H, Zhao ZJ, Liu HY, Cai J, Lu QK, Ji LD, et al. The melatonin receptor 1B gene links circadian rhythms and type 2 diabetes mellitus: an evolutionary story. Ann Med. 2023;55(1):1262\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCagnacci A, Arangino S, Renzi A, Paoletti AM, Melis GB, Cagnacci P, et al. Influence of melatonin administration on glucose tolerance and insulin sensitivity of postmenopausal women. Clin Endocrinol (Oxf). 2001;54(3):339\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRubio-Sastre P, Scheer FAJL, G\u0026oacute;mez-Abell\u0026aacute;n P, Madrid JA, Garaulet M. Acute melatonin administration in humans impairs glucose tolerance in both the morning and evening. Sleep. 2014;37(10):1715\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaraulet M, G\u0026oacute;mez-Abell\u0026aacute;n P, Rubio-Sastre P, Madrid JA, Saxena R, Scheer FAJL. Common type 2 diabetes risk variant in MTNR1B worsens the deleterious effect of melatonin on glucose tolerance in humans. Metabolism. 2015;64(12):1650\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLyssenko V, Nagorny CLF, Erdos MR, Wierup N, Jonsson A, Sp\u0026eacute;gel P, et al. 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Perspect Clin Res. 2021;12(3):171\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-clinical-nutrition","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ejcn","sideBox":"Learn more about [European Journal of Clinical Nutrition](http://www.nature.com/ejcn/)","snPcode":"41430","submissionUrl":"https://mts-ejcn.nature.com/cgi-bin/main.plex","title":"European Journal of Clinical Nutrition","twitterHandle":"@ejcneditor","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Type 2 diabetes, MTNR1B genotype, postprandial glucose, breakfast","lastPublishedDoi":"10.21203/rs.3.rs-8678875/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8678875/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe risk allele (G) of \u003cem\u003eMTNR1B\u003c/em\u003e rs10830963 has been associated with impaired glucose tolerance, increased fasting glucose and type 2 diabetes (T2D). Late evening eating, when endogenous melatonin levels are elevated, is associated with impaired glucose control in \u003cem\u003eMTNR1B\u003c/em\u003e risk carriers. Endogenous melatonin levels remain elevated into the morning so may influence glucose response to breakfast.\u003c/p\u003e\u003cp\u003e\u003cb\u003eObjective\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo investigate the interaction of \u003cem\u003eMTNR1B\u003c/em\u003e genotype and type of breakfast on postprandial glucose response.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFollowing an overnight fast, participants consumed either a standard carbohydrate-rich or protein-enriched porridge breakfast. Post-prandial glucose levels were recorded for two hours using a continuous glucose monitor (CGM). One week later, participants repeated the protocol consuming the alternate breakfast. A two-way mixed ANOVA determined the effect of breakfast and genotype on post-prandial glucose levels.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFifty-four adults completed the study. Fasting glucose was significantly higher (p\u0026thinsp;=\u0026thinsp;0.008) in GG (5.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43 mmol/L) compared to CC or CG participants (5.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42 and 5.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52 mmol/L). Post-prandial iAUC was significantly greater following the carbohydrate-rich breakfast compared to the protein-enriched breakfast (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Following the carbohydrate-rich breakfast iAUC was significantly greater in GG participants compared to CC (p\u0026thinsp;=\u0026thinsp;0.026) and CG participants (p\u0026thinsp;=\u0026thinsp;0.029). There was no significant difference between genotype groups following the protein-enriched breakfast (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe study findings demonstrate, in a relatively young and healthy population, \u003cem\u003eMTNR1B\u003c/em\u003e genotype significantly affects markers associated with T2D risk. Personalised genotype-based advice to adjust timing and composition of meals consumed when endogenous melatonin levels are increased may reduce subsequent T2D risk.\u003c/p\u003e","manuscriptTitle":"Interaction of melatonin receptor 1B (MTNR1B) genotype and type of breakfast (protein-enriched v carbohydrate-rich) on postprandial glucose response: a randomised crossover trial.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-13 12:25:45","doi":"10.21203/rs.3.rs-8678875/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2026-04-07T08:52:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-04-02T18:19:17+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-03-31T15:56:07+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-03-18T15:30:45+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-03-09T14:38:03+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2026-02-10T01:08:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-01T12:43:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-01T12:42:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Clinical Nutrition","date":"2026-01-29T09:33:47+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2026-01-28T16:23:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-clinical-nutrition","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ejcn","sideBox":"Learn more about [European Journal of Clinical Nutrition](http://www.nature.com/ejcn/)","snPcode":"41430","submissionUrl":"https://mts-ejcn.nature.com/cgi-bin/main.plex","title":"European Journal of Clinical Nutrition","twitterHandle":"@ejcneditor","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"dabeb21a-6c25-4dfe-a4fd-cc10544e6523","owner":[],"postedDate":"February 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":62622902,"name":"Health sciences/Diseases/Endocrine system and metabolic diseases/Diabetes/Type 2 diabetes"},{"id":62622903,"name":"Biological sciences/Genetics/Population genetics/Genetic variation"}],"tags":[],"updatedAt":"2026-04-21T21:32:46+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-13 12:25:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8678875","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8678875","identity":"rs-8678875","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}