Lepidium meyenii Walp.) is a traditional Andean crop with great potential for various sanitarian and medical functions, which is attracting increased research attention. The majority of previous Maca studies were focused on biochemistry and pharmacodynamics, while the genetic basis of its unique characteristics lagged due to a lack of genome information. The authors perform gas chromatography-mass spectrometry (GC/MS) analysis in the hypocotyls of three Maca ecotypes and identify 79 compounds. Among them, 62 compounds have distinct profiles among Maca ecotypes. To reveal the underlying regulatory mechanism of the chemical composition differences, de novo transcriptome sequencing is performed and the transcription profiles of three Maca ecotypes are comparatively analyzed. Functional analysis indicates several key pathways, including “starch and sucrose metabolism,” “phenylpropanoid biosynthesis,” “phenylalanine metabolism” and “plant-pathogen interaction,” are involved in regulating the chemical compositions of Maca. Combining metabolomics and transcriptomics analysis indicates transcription factors such as MYB and WRKY and mediators such as protein kinase and bifunctional inhibitors might be critical regulators of chemical composition in Maca. The transcriptome reference genome and differentially expressed genes (DEGs) obtained in this study might serve as an initial step to illustrate the genetic differences in nutrient component, secondary metabolites content, medicinal function and stress resistance in Maca.Maca ( Lepidium meyenii Walp., commonly known as Maca, belongs to the Brassicaceae family. It is a traditional Andean crop that grows at altitudes between 3500 and 4500 m above sea level, in the central region of Peru [ of Peru . Maca is of Peru . Since tN-hydroxypyridine, referred to as Macaridine, the benzylated alkamides (Macamides) and Macaenes (unsaturated fatty acids) are chemotaxonomically unique compounds of Maca [The modified hypocotyl is the main edible part of Maca. The chemical composition and nutritional value of Maca hypocotyls have been investigated extensively. Compared to other tuber plants such as potatoes and carrots, Maca has a higher content of protein, fiber and unsaturated fatty acid. The amino acid composition of Maca has an excellent human nutritional profile and the content of essential amino acids is higher in Maca than in potatoes or carrots . The maj of Maca . The increasing popularity of Maca owes largely to its powerful effects on the improvement of fertility and sexual behavior. Pharmacological studies showed that Maca extracts improved sexual behavior in male rats and mice ; the effDifferent ecotypes of Maca are described according to the color of their hypocotyls. There are 13 known ecotypes of Maca in the Junin region of Peru, ranging from white to black in color . AccordiAs a “neglected crop” with excellent potential applications, Maca is attracting increasing research attention. However, Maca studies to date have largely focused on the biochemistry, nutriology and pharmacology levels; the genome data were available for Maca until recently . To inteAll Maca plants were planted in the Maca planting center in the same field of Dahai village , Huize county, Yunnan province, China, where annual average temperature is 12.7 °C and annual rainfall is 800 to 1000 mm, in March of 2014. The hypocotyls, which were randomly collected in January of 2015, were all similar in size and were all free of disease, damage and decay. Six hypocotyls were sampled for each ecotype. The overground parts of the Maca plants were removed and the hypocotyls were quickly cleaned under running water. Then the samples were immediately frozen in liquid nitrogen and stored at −80 °C until used.v/v/v) with 15 μL (2 mg/mL) of vanillic acid as an internal standard). All extracts were sonicated for 1 h and then centrifuged at 15,000 rpm at 4 °C for 10 min. The supernatant (1.3 mL) was transferred to a new 1.5 mL tube and then centrifuged at 15,000 rpm at 4 °C for another 10 min, when 500 μL of new supernatant was collected by a conical insert of a 2 mL glass vial and dried under nitrogen flow on an N-EVAP Nitrogen Evaporator. The silylation reaction to increase the volatility of the metabolites was conducted by adding 50 μL of N,O-Bis (trimethylsilyl) trifluoroacetamide (BSTFA) to the sample and then incubating it for 60 min at 50 °C. The freshly frozen tissues were ground to powder in liquid nitrogen, filtered using a 40-mesh sieve and stored at −80 °C until the metabolic study. The samples were passed through lyophilization prior to further treatment. The tissue powder (20 mg) was added to a 2 mL tube and soaked in 1.5 mL of an extraction solvent  model was selected to achieve ionization of the metabolites at 70 eV.To perform metabolomic analysis, six hypocotyls for six biological replicates per ecotype were used. GC-MS analysis was performed on an Agilent 7683B series injector  coupled to an Agilent 6890N series gas chromatograph system and a 5975 mass selective detector (MSD) . Agilent DB-5MS column  was applied. The column process was as follows: temperature was 70 °C for 4 min and then increased at 5 °C /min to 310 °C for 15 min. The injection temperature was set at 300 °C and the injection volume was 1 μL with a 10:1 split ratio by applying Helium  as a carrier gas. The column was equipped with a linear velocity control model at 1.2 mL/min. Prior to the instrumental analysis, the mass spectrometer was tuned using perfluorotributylamine (PFTBA) to obtain optimum performance. A simultaneous full scan-selected ion monitoring mode (Scan-SIM) was used to acquire the data. The mass spectra scanning scope was set to 33–600 For RNA extraction, the same six hypocotyls were sampled and randomly divided into two groups for each ecotype, representing two biological repeats. The mixed samples were named b1 and b2 (black Maca), y1 and y2 (yellow Maca) and v1 and v2 (violet Maca) . The totTo construct the library, the NEB Next Poly (A) mRNA Magnetic Isolation Module  was used to accomplish the poly (A) mRNA isolation, fragmentation and priming. First strand complementary DNA (cDNA) was synthesized using ProtoScript II Reverse Transcriptase (NEB) and Second Strand Synthesis Enzyme Mix (NEB) were used to synthesize first strand cDNA and second strand cDNA, respectively. AxyPrep Mag PCR Clean-up  was used to further purify Double-stranded cDNA. Then, End Prep Enzyme Mix (NEB) was applied to add adaptors. AxyPrep Mag PCR Clean-up kit (Axygen) was used to recover fragments of ~400 bp (with the approximate insert size of 250 bp). Each sample was then amplified by PCR according to instructions. The PCR products were purified and then validated using an Agilent 2100 Bioanalyzer  and quantified via Qubit and real time PCR analysis . Sequencing was carried out using a 2 × 125 paired-end (PE) configuration with Illumina HiSeq 2500 instrument according to the manufacturer’s instructions  The sequences were processed and analyzed with GENEWIZ software .Clean data were obtained by removing reads containing adapters, reads containing ploy-N and low-quality reads from the raw data. The clean reads were assembled into contigs using the Trinity method with an optimized k-mer length of 25 for de novo assembly . Accordi−5. Additionally, by using the Blast2GO  program, GO (Gene Ontology) terms were extracted from the best hits obtained from BLASTx analysis against the Nr [−5) to predict possible functional classifications and molecular pathways.The final assembled unigenes were searched against the Nr (NCBI non-redundant protein sequences) database to identify putative gene functions using the BLAST algorithm  with an t the Nr . The unit the Nr   , all rea2 > 0.9 were selected. The relationships between metabolome and transcriptome data were demonstrated by using Cytoscape .Pearson correlation coefficients were calculated for metabolome and transcriptome data integration. The authors calculated the mean content of metabolites of Maca ecotypes and the mean value of transcript abundance of DEGs together. The coefficients were calculated from log2 (fold change) of each metabolite and log2 (fold change) of each transcript. Correlations corresponding to a coefficient with R® Premix Ex Taq™ II , ROX plus . The 2−ΔΔCT method [Total RNA was reverse transcribed to generate the first strand cDNA using a PrimeScript™ RT reagent Kit with gDNA Eraser . The cDNA was diluted 1:4 in distilled water and used as template for qPCR. The Maca actin gene (LmActin) was used as an internal control for normalization. The qPCR reaction was performed on an ABI 7500 qPCR instrument. Real-time PCR reactions were performed using SYBRT method  was usedGas Chromatography–Mass analysis was used to evaluate the metabolite composition in Maca hypocotyls. Comparing the mass spectra of analyte peaks with those of commercial reference standard compounds identified a total of 79 metabolites . The datThrough the combining of the VIP (variable importance in the projection) values in the loadings plot , metabolAmong the 62 differentially accumulated metabolites, 14 compounds were identified to have different content in all analyzed Maca ecotypes, including six amino acids , four carbohydrates , three organic acids  and one fatty acid (stearic acid) . The proTo obtain a comprehensive Maca transcriptome, six cDNA samples prepared from mRNA of black, yellow and violet Maca hypocotyls were sequenced using the Illumina sequencing platform, respectively. Following removal of adaptor sequences and discarding low quantity reads, these samples generated 3.79 Gb (b1), 5.62 Gb (b2), 4.97 Gb (y1), 6.30 Gb (y2), 5.04 Gb (v1) and 5.13 Gb (v2) of quality transcriptome data. A summary of the sequencing output is presented in All high-quality reads were de novo assembled using the “Trinity” program. Further assembly was then performed with the TGICL program . Redundant sequences were removed. Finally, a total of 9.16 Gb data, containing 115,866 unigenes, was obtained; this data set included all the transcripts built from high quality reads of the hypocotyls of the three Maca ecotypes. The distribution of the sequence lengths in the data set is shown in −5) against multiple protein databases, including the NCBI non-redundant protein (Nr) database [Arabidopsis thaliana  and Arabidopsis lyrata subsp. lyrata . As a member of the Brassicaceae family, it is not surprising that Maca sequences are highly homologous to the Arabidopsis thaliana genome. This fact should greatly facilitate future studies and crop improvement efforts concerning Maca.All 115,866 unigenes were annotated using the BLAST algorithm , a chlorophyll A-B binding family protein (c21560_g1_i1), an alpha/beta-Hydrolase superfamily protein (c35506_g1_i2), a phosphatidic acid phosphatase (PAP2) family protein (c40541_g1_i1), a chalcone and stilbene synthase family protein (c40810_g1_i1) and a plastidic GLC translocator (c43742_g2_i1), respectively. The expression profiles of these genes, as measured by qPCR, were compared among the three ecotypes. The qPCR and RNA-Seq results were highly similar . WRKY, ERF, NAC, MYB and HD-ZIP gene family had the largest numbers involved. The authors noticed that GeBP, HSF, Whirly, G2-like and TALE gene were differentially expressed just between yellow and violet Maca; MYB, HD-ZIP, LBD, CO-like, ARR-B, MIKC_MADS and C2H2 genes had no significant expression difference between yellow and black Maca and the transcript abundance of the RAV gene was not significantly different between black and violet Maca  with 39 metabolites were identified. Correlation results showed 39 metabolites were divided into three groups and 140 transcripts were separated into eight clusters  and OPLS-DA, indicating the chemical composition difference among Maca ecotypes. Furthermore, the authors noticed that yellow Maca has obviously lower amino acids content, while significantly higher content of carbohydrates, organic acids and sterols than other ecotypes, suggesting that yellow Maca has higher soluble sugar content, higher long-chain fatty acid content and lower protein content. Amino acids are essential precursors of glucosinolates, which is an important active ingredient of Maca . AliphatConversely, some compounds have significantly higher content in one ecotype and might be used as marker compounds to identify Maca ecotypes—Mannose, 10,12-docosadiynedioic acid and hexanoic acid of black Maca, lactic acid, pipecolic acid and 2-pyrrolidinone of yellow Maca and β-alanine, butanoic acid and malic acid of violet Maca for example. Efficient marker compounds could be selected by screening in more Maca ecotypes. Arabidopsis thaliana, Arabidopsis lyrata and another tuber root plant Brassica rapa, respectively (data not shown). The present genome information of Maca will facilitate the further studies on the regulatory mechanism of tuber root formation in the cruciferae family.The authors obtained 115,866 unigenes of Maca hypotocyl and 63.10% of them were annotated. GO, COG and KEGG analysis indicated that the transport and metabolism of amino acids and carbohydrates were actively occurring in Maca hypotocyls, which confirmed it as a nutrient rich organ. Additionally, searching Maca unigenes against the transcriptome data of other Cruciferae members showed that the unigene sequences of Maca has a relatively high similarity to the genome data of The Kyoto Encyclopedia of Genes and Genomes analysis of DEGs showed that pathways of starch and sucrose metabolism, phenylpropanoid biosynthesis and phenylalanine metabolism include the largest number of DEGs. It is consistent with the results from metabolome data that Maca ecotypes have distinct profiles of the derivates of starch and sucrose metabolism. Phenylpropanoid biosynthesis is a key process for the biosynthesis of an enormous array of secondary metabolites, such as coumarins, tannins, lignin and flavonoids . PhenylaIt is remarkable that DEGs between black and yellow Maca enriched in the pathway of “plant-pathogen interaction,” and a lot of “response to disease” and “disease resistant” genes were identified as DEGs between black and yellow Maca, indicating that the two ecotypes have different sensitivity or resistance to biotic stress. Combining with the fact that yellow Maca is the most widely planted ecotype with the largest yield, while black Maca is lowest in yield and demand to cultivate , it implThe authors discovered some genes especially expressed in one or two Maca ecotypes, which, at least partially, represent certain properties of the ecotype/s. The DNA ligase genes only expressed in black Maca suggest the occurrence of DNA damage and repair events . The genThe authors conducted a GC-MS-based metabolome analysis and de novo transcriptome sequencing of hypocotyls of Maca ecotypes. It was verified that different Maca ecotypes have distinct metabolic compositions and expression profiles. Yellow Maca is rich in carbohydrates and unsaturated fatty acid, black Maca is rich in protein and glucosinolate and violet Maca showed better antioxidant capacity. DEG analysis suggested that Yellow Maca have stronger resistance to disease, which might be a critical reason for its wide cultivation. MYB and WRKY transcription factors might play important roles in chemical composition determination of Maca. Genes encoding DNA ligase, ultraviolet-B receptor and chalcone synthase, as well as metabolites such as mannose, lactic acid and β-alanine, are candidate markers for Maca identification. While this study is a preliminary investigation on the chemical composition difference and underlying transcriptional regulation in Maca ecotypes, the further work to decipher the difference among ecotypes needs more experimental replicates for minimization of environment impacts. In addition, the measurement of anthocyanin content would be beneficial to directly distinguish the Maca ecotypes in the future. Overall, the genome resources generated in the present study will be valuable for further genetic and molecular investigations of Maca and lay the foundation for the use of modern molecular methods in efforts to improve the development and utilization of this species.


Aims: The objective of this study was to identify the determinants of glycaemic control among people with type 2 diabetes mellitus in Bangladesh. A cross-sectional study was carried out during March to September 2017, and 1253 adult patients with type 2 diabetes mellitus were recruited from six hospitals. Data were collected from patients via face-to-face interview, and their medical records were reviewed. Multiple logistic regression analysis was performed. Among the participants, 53.2% were male. Mean (±SD) age was 54.1 (±12.1) years and mean (±SD) duration of diabetes was 9.9 (±7.2) years. About 82% participants had inadequate glycaemic control (HbA1c ≥ 7%) and 54.7% had very poor control (HbA1c ≥ 9%). Low education level, rural residence, unhealthy eating habits, insulin use, infrequent follow up check-ups and history of coronary artery diseases found associated with inadequate and very poor controls. Being female and smokeless tobacco consumer appeared to be associated with inadequate control however cognitive impairment was associated with very poor control only. Prevalence of inadequate glycaemic level was very high in Bangladesh. Having understood relatable lifestyle modification factors, demographics and co-morbidities among people with type 2 diabetes, health care providers in conjunction with patients should work together to address the glycaemic control. In Bangladesh, the prevalence of diabetes was 9.7% in 20112, and the number of adults with diabetes is projected to be 13.7 million by 20451.Diabetes is one of the biggest health threats of recent times for the global population, rich and poor alike. It was estimated that, in the year 2017, more than 425 million people globally were suffering from diabetes. The burden is increasing, predominantly in low- and middle-income countries, where about 80% of total diabetes deaths in the world occur1.A major concern of diabetes is the complications that accompany it, which occur as detrimental consequences of hyperglycaemia. Long-term hyperglycaemia may cause damage in various organs and can lead to the development of disabling and life-threatening complications such as cardiovascular disease, neuropathy, nephropathy and retinopathy. In 2017, a total of US$727 billion was spent globally to treat and prevent diabetes and its related complications6 have revealed that strict control of glycaemic levels helps to prevent complications, especially of the microvascular type, and that these complications are directly related to quality of life8.The most important aspect of the optimal management of patients suffering from diabetes is prevention of the injurious effects of hyperglycaemia. Glycaemic control is thus considered as the main therapeutic goal for prevention of these severe consequences. Results from many observational studies and randomised controlled clinical trials14 have identified several factors that are related to poor glycaemic control. However, most of these studies have been conducted on patients in Western countries. A paucity of such evidence exists for resource-limited populations such as Bangladesh, where diabetes presents a huge burden that goes unnoticed to a large extent. Only one study15 has been conducted in Bangladesh attempting to identify the risk factors related to poor glycaemic control; however, it addressed a limited number of factors compared to studies undertaken in Western countries. In order to provide effective research-based evidence, the relationships between poor glycaemic control and all potentially important factors, including compliance with management plans, the effects of lifestyle modification factors, family support, anxiety, depression, and cognitive function, need to be investigated. Thus, the objective of the current study is to estimate the prevalence of glycaemic control, and to widen the investigation regarding related factors, among patients with T2DM in Bangladesh.Optimal control of glucose is a daunting task without a clear understanding of the precise dynamics of poor glycaemic control in people with type 2 diabetes (T2DM). Epidemiological studies in different populationsA cross-sectional survey was carried out in Bangladesh from March to September 2017. Data were collected from six hospitals across the country. The selected hospitals are all affiliated with the Diabetic Association of Bangladesh (BADAS), the largest diabetes care provider in the country. All of the hospitals provide various levels of care to people with diabetes. Hospitals affiliated with BADAS are located both inside and outside metropolitan areas across the country, covering rural, urban, and semi-urban settings. Within metropolitan areas, the selected hospitals are the central hospitals that provide primary to tertiary care services. The hospitals outside metropolitan areas usually provide primary to secondary care; hence, patients attending these hospitals but in need of tertiary care are usually referred to the metropolitan hospitals. Using a selection of these specific hospitals for this study allowed for recruiting a heterogeneous sample.15 obtained from a previous Bangladeshi study on T2DM, a sample size of 938 patients was calculated. However, a total of 1253 patients, aged ≥18 years, all registered with BADAS and having been T2DM patients for a minimum duration of one year, were recruited for the study. The study excluded people suffering from other types of diabetes.Using 95% confidence level and 5% significance levels, a margin of error of 2.5% for the prevalence of good glycaemic control of 18.8%Each patient was interviewed face-to-face using a pre-tested questionnaire after informed written consent was obtained prior to the interview. The questionnaire was pre-tested through a pilot survey in the Bangladesh Institute of Health Sciences hospital. The first section of the questionnaire consisted of questions about patients’ socio-demographic and lifestyle characteristics, including age, gender, marital status, education, profession, monthly household income, smoking status, eating habits, and physical activity. The next section of the questionnaire consisted of clinical and diabetes-related information about the participants such as duration of diabetes, family history of diabetes, frequency of follow-up check-ups, mode of treatment, and hypoglycaemic events. A data extraction checklist was used to collect the data from patients’ records, including laboratory test results, diagnosis, medications, history of complications, and comorbidities.16 was used, with some minor modifications to make it suitable for the Bangladeshi population. Six selected items from the Global Physical Activity Questionnaire (GPAQ)17 were used to assess physical activity levels. Patient Health Questionnaire-2 (PHQ-2)18, Generalized Anxiety Disorder Scale (GAD-2)19, Michigan Neuropathy Screening Instrument20, and a Six-item cognitive impairment test (6CIT)21 were used, all without any modification. Permissions were obtained from the respective authorities to use the above-mentioned tools. The weight and height of participants were measured while they were wearing light clothes and no shoes. Waist and hip circumference were measured against thin clothing. Body mass index (BMI) and waist-hip ratio (WHR) were calculated from the collected measurements. Research Electronic Data Capture (REDCap) was used to collect and manage the data22.The final section of the questionnaire was tailored, including the use of several recognised tools to assess a variety of factors known and alleged to relate to aspects of diabetes control. The UK diabetes and diet questionnaire (UKDDQ)23; fair control = HbA1c 7–8%; and poor control = HbA1c > 8.0%24. An HbA1c cut-off value of ≥9% was used to represent very poor control25. BMI was categorised as: <18.50 = underweight; 18.50–24.99 = normal; >25.00 = overweight or obese26. The cut-off point for WHR was defined as a ratio of >0.90 for men and >0.80 for women27. Hypertension was defined by either a documented diagnosis of hypertension, the patient taking antihypertension medications, or the latest (within three months) blood pressure readings (either systolic ≥140 or diastolic ≥90)28. Dyslipidaemia was defined based on either a documented diagnosis of dyslipidaemia or the patient taking any lipid-lowering medications. Impaired cognitive function was defined as a score of more than seven using 6CIT21. Neuropathy was defined as a score of seven or more using the Michigan Neuropathy Screening Instrument20. Diabetic foot was confirmed by visual examination of ulcers or amputations and a documented diagnosis of diabetic foot. Physical activity was measured using the GPAQ, and >150 minutes of walking per week was considered as active. Dietary habits were assessed using the UKDDQ16. The dietary habit variable was measured on a scale between 0 and 48 and categorised using a cut-off at the first quartile (score 28). A score higher than 28 was considered to indicate healthy eating habits.The patient’s latest readings (within the previous three months) of glycaemic status were categorised as follows: good glycaemic control = HbA1c < 7%19.The project was approved by the Monash University Human Research Ethics Committee and the Ethical Review Committee of the Bangladesh University of Health Sciences. Approval was also obtained from BADAS. All the study procedures were carried out in accordance with the principles of the Declaration of Helsinki as revised in 201329. Data were analysed using the statistical software package STATA SE version 15.Descriptive statistics were reported using mean with standard deviation (SD) for numerical data and relative frequencies (percentages) for categorical data. To test the associations between risk factors and levels of glycaemic control, ANOVA, chi-square tests, and simple logistic regression analysis were used for a univariate analysis. Risk factors with a p-value < 0.05 in simple logistic regression analysis were considered for a multiple logistic regression model. Clinically plausible risk factors were entered into the model even if they appeared to be insignificant in the univariate analysis. Multi-collinearity and the first-order interaction effects between clinically relevant risk factors were investigated. A step-wise backward elimination method was used to select variables that were significantly related to the outcome measures. Multiple logistic regression analysis was mainly performed to identify the determinants for an inadequate glycaemic level (HbA1c ≥7%) as well as for very poor glycaemic control (HbA1c ≥9%). In order to determine the duration-specific risk factors, the patients were stratified by the T2DM durations of: ≤5 years and >5 yearsAmong the participants, 532 (53.2%) were male. The mean (±SD) age was 54.1 (±12.1) years and the mean (±SD) duration of participants’ diabetes conditions was 9.9 (±7.2) years. The mean (±SD) BMI was 25.7 (±4.9) kg/m² and the mean (±SD) HbA1c was 9.0% (±2.2%). Only 18.8% of participants were classified as having good control, 19.78% had fair control, 62% had poor glycaemic control, and 54.7% had very poor control. Table The associations between various clinical characteristics and glycaemic control are presented in Table The results of multiple logistic regression analysis with step-wise removal for inadequate glycaemic control HbA1c ≥7%) and very poor glycaemic control (HbA1c ≥9%) are presented in Fig. c ≥7% andThe sub-group  analysis results for inadequate and very poor glycaemic controls are presented in Tables The sub-group analysis performed for very poor glycaemic control showed more differentiated risk factors than shared ones between the two groups, as shown in Table Glycaemic control is the cornerstone of managing T2DM and is essential for the prevention of long-term diabetes complications. The key result of this study is that 81.8% of participants did not achieve the recommended HbA1c target of lower than 7%, and 54.7% showed very poor control (HbA1c ≥9%). In general, being female, a low level of education, rural residence, smokeless tobacco consumption, unhealthy eating habits, insulin use, history of CAD, and cognitive impairment were associated with inadequate glycaemic levels in the Bangladeshi T2DM population. Additionally, different sets of risk factors played pivotal roles in the two sub-groups formed based on different durations of T2DM. The cross-sectional nature of the study may not provide reliable insights on temporal relationships; however, the identified association between various factors and glycaemic control is certainly worthy of mention.et al.15 and Latif et al.30. The proportion of people with inadequate glycaemic control is higher among females who have had the condition for a longer duration (>5 years), which is also similar to the findings of the previous studies29. This may be because the females who were in the longer duration group in the current study sample were comparatively older, less compliant with healthy eating, and were being treated with insulin. All of these factors pose individual risks for poorer control. The current study shows that the proportion of people with inadequate glycaemic control is higher among people with a low level of education and those living in rural areas, which is also supported by the previous studies32. People living in a rural area are likely to have a low level of education, and thus have lower levels of T2DM knowledge, low self-management behaviours, low self-efficacy, and low continuity of care. Furthermore, a low level of education increases the likelihood of being in a lower socio-economic class, which may limit their ability to access adequate health care facilities. Due to limited accessibility and affordability, they may not visit a diabetes specialist until they experience complications in the progression of their diabetes. On the other hand, people with a better education and living in urban areas usually have a higher income; thus, they are more likely to be able to afford to receive proper treatment and manage their condition.The prevalence of inadequate glycaemic control found among people with T2DM is consistent with previous studies conducted in Bangladesh by Selim 33. However, the effect of smokeless tobacco on glycaemic control has not yet been documented in the literature. Thus, an intensive investigation is urgently required in Bangladesh, as well as in other South Asian countries where smokeless tobacco consumption is a common practice. Further, education and awareness programs about the risks of smokeless tobacco consumption could be an option for the management of T2DM.The proportion of participants in the current study who are smokeless tobacco users was 22.35%, and the results of the sub-group analysis showed that smokeless tobacco consumers among the shorter duration group were at higher risk of having an uncontrolled glycaemic level. Smokeless tobacco consumption in the form of betel quid (pan) is very common in Bangladesh, especially among women living in villages. Tobacco usually raises blood sugar levels, and the adverse effects of smokeless tobacco on health are evident from previous studies28. Conversely, a relationship was identified between unhealthy eating habits and both inadequate and very poor glycaemic control. Clinical trials34 and epidemiological studies14 have shown the positive effects of healthy diets on glycaemic control. The majority of the current study’s participants responded that they had received dietary advice from health professionals; however, they also stated that they were unable to maintain the advice. This may be due to a lack of understanding or low affordability of healthy foods. Regular follow-up check-ups add an extra benefit in terms of better control and, similar to previous studies35, our findings indicate that regular follow-up check-ups have a positive effect on glycaemic control. Thus, active and individualised education intervention is required to motivate patients towards healthy eating and frequent follow-up check-ups.A healthy lifestyle with regular physical activity and healthy eating habits are very important factors for achieving and maintaining adequate glycaemic control. This study found that participants were active in following the recommended guidelines11. Possible reasons for this could include the increasing difficulty of taking multiple medications, injection phobia, or inconvenience of insulin use. Additionally, the efficacy of insulin depends on storage conditions and its proper use, and appropriate dosage in response to different glycaemic levels depends on an individual’s eating habits, exercise regimens, and other lifestyle factors. Insulin users may also have a more progressive disease condition that requires more aggressive treatment, and physicians may attempt dual therapies to achieve better control. Additionally, we found that only 37.6% of our participants used self-monitoring blood glucose devices; this indicates that a lack of proper monitoring, meaning that patients are likely to struggle with managing their insulin. In this context, further research is required to determine why a large proportion of insulin users were identified as having uncontrolled conditions.Treatment modality also influences the outcome of glycaemic control. In this study, the best glycaemic control was found among participants who used OHA only. Notably, none of the study participants were using insulin pumps or continuous glucose monitoring. A relationship between insulin use and glycaemic control was found in the study results, which is consistent with the findings of other studies14. In general, patients with CVD are treated with multiple medications, and some of these may have an adverse effect on glycaemic control. Thus, patients with CVD have a lower likelihood of controlling their condition. The identified relationship between CVD and glycaemic control reinforces the need to optimise the management of CVD.Our results also show a relationship between glycaemic control and the presence of CAD. A systematic review investigating factors associated with glycaemic control showed a 48% increased risk of having poor condition control in the presence of CVD38 have shown that there is a strong relationship between poorly controlled diabetes and greater decline in cognitive function. However, no similar study has been conducted in developing countries. Previous literature shows that the toxic effects of chronic hyperglycaemia may be related to slowly progressive functional and structural abnormalities in the brain39, and thus could be one of the determinants of cognitive changes in people with diabetes41; which may not be confirmed by the current study due to its cross-sectional design. Additionally, insulin resistance, at least in the early stages of type 2 diabetes, is associated with compensatory hyperinsulinemia and the consequent accelerated cognitive decline42, which supports the findings of our study.Another important finding of this study is the association between impaired cognitive function and poor glycaemic control among patients with a longer duration of T2DM. Studies conducted previously in developed countriesThis study has the strength of having a representative population, which increases the likelihood of the generalisability of the findings to people with T2DM attending hospitals associated with BADAS across the country. The study investigated all possible modifiable and non-modifiable factors affecting glycaemic control, which adds strength to the findings. The recruitment of participants and the information collection procedures ensured data quality. However, this study has the limitation of being cross-sectional in design, meaning that a temporal relationship between cause and effect cannot be established.In conclusion, the proportion of people with uncontrolled glycaemic levels is considerably high in Bangladesh, which may contribute to an increasing prevalence of complications and thus may pose an extra burden on health care costs. This study has identified a number of modifiable predictors of inadequate glycaemic control: most importantly, different sets of risk factors were identified for participants who had been T2DM patients for different durations. The study’s findings emphasise the importance of being compliant with follow-up check-ups, and of lifestyle modifications, including healthy eating and avoiding smokeless tobacco consumption. A comprehensive knowledge of modifiable and non-modifiable risk factors will help health care providers to individualise the choice of glycaemic goals in reference to duration, with the aim of improving care and outcomes for patients with T2DM.


APC and MUTYH are high penetrance predisposition genes for adenomatous polyposis, but they only account for 5–10% of AAP. Other new predisposition genes, such as POLE, POLD1, NTHL1, AXIN2 or MSH3, have been recently described and have been associated with AAP, but their relative contribution is still not well defined. In order to evaluate the genetic predisposition to AAP in a hospital based population, germline DNAs from 158 AAP subjects were screened for genetic variants in the coding regions and intron-exon boundaries of seven associated genes through a next-generation sequencing (NGS) custom gene panel. Splicing, segregation studies, somatic mutational screening and RNA quantitative expression assays were conducted for selected variants. In four of the probands the adenoma susceptibility could be explained by actionable mutations in APC or MUTYH, and one other patient was a double carrier of two truncating variants in both POLE and NTHL1. Furthermore, 16 additional patients harbored uncertain significance variants in the remaining tested genes. This report gives information about the contribution of the newly described adenomatous polyposis predisposition genes in a Spanish attenuated polyposis cohort. Our results highly support the convenience of NGS multigene panels for attenuated polyposis genetic screening and reveals POLE frameshift variants as a plausible susceptibility mechanism for AAP.Attenuated adenomatous polyposis (AAP) is a heterogeneous syndrome in terms of clinical manifestations, heritability and etiology of the disease. Genetic heterogeneity and low penetrance alleles are probably the best explanation for this variability. Certainly, it is known that  Adenoma burden can be low or mild, it may be accompanied by hyperplastic or serrated polyps, the polyposis diagnosis age is variable and later than classical forms, and CRC risk can range from 40% to 80% depending on the adenoma burden. A positive family history is frequently absent, but horizontal or vertical inheritance patterns are also observed. The diffusion of early detection CRC screening programs, together with the improvement of colonoscopy techniques, has given rise to an increase in the detection of patients with multiple colorectal adenomas. These patients are referred to the oncogenetic counseling units for genetic testing in order to find an explanation to their adenoma susceptibility that helps in the understanding of the disease and makes possible a satisfactory genetic counseling. Nowadays, APC (MIM *611731) and MUTYH (MIM *604933) are the two main clinical actionable predisposition genes for adenomatous polyposis3. That means prevalence and cancer risk estimations are well-defined, allowing an accurate genetic counseling and effective high risk monitoring programs for carriers. They both together explain the vast majority of classical adenomatous polyposis (>100 adenomas), but they are only able to explain a small fraction of AAP2. In fact, in our hospital settings, we are not able to explain more than 5–10% of the patients referred to our laboratory after the routine genetic tests. Therefore, the identification of the underlying susceptibility causes of those unexplained AAP cases is a priority in our laboratory.Attenuated adenomatous polyposis (AAP) is usually defined by the presence of more than 10 and less than 100 adenomas along the large intestine and/or rectum. It is a highly heterogeneous syndrome in terms of polyposis severity, family history, and lifetime risk of colorectal cancer (CRC)POLE4, POLD14, NTHL15, MSH36and AXIN27 , have been described. However, they are still not well characterized and only a few reports have attempted to estimate the extent to which some of these genes, individually, are involved in different CRC populations13. Therefore, they are still poorly implemented in the daily clinical practice.Recently, other adenomatous polyposis predisposition genes, such as APC, MUTYH, POLE, POLD1, NTHL1, MSH3 and AXIN2 in a cohort of AAP collected at our oncogenetic counseling unit. The main objective of this work is to determine the contribution of the AAP associated genes in an unexplained AAP cohort.Under this scenario of high genetic heterogeneity, the use of next-generation sequencing (NGS) gene panels for the diagnosis of hereditary AAP seems to be the best choice. Aiming to delve into the genetic study of unexplained AAP, we have screened the whole coding sequences and intron-exon boundaries of A clinical description of the study cohort is summarized in Table APC) and NM_00128425.1: exon 15 (MUTYH). Once the screening was completed, 28 variants located in six genes were validated in 24 patients  analysis, NM_000038.4: exon 13 : Two patients harbored class-5 variants in -3 Table .MUTYH variants  and c.1510_1517delinsCCAACAGCCA; p.Thr504Profs*68) as likely pathogenic (class-4) and pathogenic (class-5), respectively, and to reclassify the variant POLD1: c.2007-5C > T as benign (class-1) and POLE: c.6716C > T p. as likely benign (class-2)  Table . In the MUTYH variant c.739C > G; p.(Arg247Gly) was detected in trans  was reclassified as class-4 (Suppl. Table MUTYH variant c.1510_1517delinsCCAACAGCCA p.(Thr504Profs) was detected in trans  was detected in homozygosis in both an affected and a healthy member, and it was absent in another affected member. Therefore, it was reclassified as class-2 variants.POLE:c.141delG; p.Phe48Leufs*6 and NTHL1:c.268C > T; p.Gln90*, were detected in the same germline DNA , whereas two mutations were detected in genes involved in later stages .In order to investigate the involvement of these variants in the adenoma and CRC formation, four adenomas  and one adenocarcinoma (Haggit-0) (83AC1) from the proband were analyzed for somatic mutations , one adenocarcinoma (83AC1) and healthy colon tissue from the proband (83COLON). POLE wild type allele expression in the carrier’s colon tissue (83COLON) did not show a significant change compared to the colon control pool (fold difference (FD) = 0.94 ± 0.27, ρ = 0.82), whereas NTHL1 wild type allele expression in 83COLON did .In addition, POLE and NTHL1 transcripts were over-expressed in the CRC control pool . However, all adenomas and the adenocarcinoma tested from the carrier showed a decrease in the expression of POLE wild type allele , whereas NTHL1 wild type allele showed significant over-expression in one adenoma and one adenocarcinoma from the proband when compared to its healthy tissue   Fig. .MUTYH and APC is recommended in those cases with more than 10 adenomas18. The diagnostic approach in our hospital consists in the screening of the four most prevalent MUTYH mutations in Spanish population19, c.536A > G; p.(Tyr179Cys), c.1187G > A; p.(Gly396Asp), c.1227_1228dup; p.(Glu410Glyfs*43) and c.1437_1439delGGA; p.(Glu480del), and the subsequent screening of point mutations and copy number variations (CNVs) in the whole coding sequence of the APC gene in those cases with a higher polyp burden and high suspicion of inheritance pattern. However, by this approach we are only able to explain around 5% of the cases with more than 10 adenomas, or 7% when restricting the criteria to full-blown polyposis (more than 20 adenomas or 10 synchronous adenomas). In order to improve the diagnostic sensitivity and investigate the contribution of currently known high-penetrance adenomatous polyposis genes in our AAP population, we have conducted a genetic screening in an unexplained AAP cohort through a custom gene panel, including APC, MUTYH, POLE, POLD1, NTHL1, AXIN2 and MSH3 coding regions.AAP is becoming one of the largest groups of patients attending our Genetic Counselling Unit. Genetic screening of APC and MUTYH. However, only POLD1 and POLE were tested on a subset of the adenoma cohort, and the remaining adenomatous polyposis predisposition genes  were not tested20. Therefore, this is the largest multiple polyposis cohort in which joint genetic screening for the full coding sequences of all AAP predisposition genes has been done so far.Our study cohort was made up of 158 subjects, 132 (83.5%) of which fulfilled the clinical criteria for full-blown polyposis  and c.1510_1517delinsCCAACAGCCA p.Thr504Profs*68, both in co-occurrence with the recurrent mutation c.1187G > A; p.(Gly396Asp), being able to explain the polyposis susceptibility in two more subjects . However, 10 uncertain significance (class-3) variants were detected in AXIN2, NTHL1, POLD1 and POLE  in any of the genes associated with new polyposis syndromes (12 (1–2% per gene), and whose probable pathogenicity might be proven during the coming years. For this reason it is important to include all these genes in the routine analysis of AAP through NGS panels.Considering other previous studies that included multiple polyposis cohorts, the frequency of actionable mutations in all of these genes seems to be very low in tested populations, but not insignificant (around 1–2%). Just like it is not irrelevant the number of variants of uncertain significance that have been described in this and other worksNTHL1 and exon two of POLE  pathway. Resembling to MUTYH-associated polyposis, germline biallelic mutations at NTHL1 have been recently associated with adenomatous polyposis predisposition5, leading to a deficiency in the repair of 5-hydroxycytosine and a consequent increase in the C > T somatic mutation rate. Like other glycosylases involved in the BER pathway, NTHL1’s repair activity can be completed by a short or long BER patch, mainly depending on the proliferative activity of the cell23. Thus, in high division rate tissues NTHL1 is coupled to the DNA synthesis and follows the long-patch BER pathway, dependent of PCNA and where POLE and POLD1 are the polymerases responsible for filling the gap after NTHL1’s action and strand cleavage23.On the other hand, POLE and NTHL1 co-occurring truncating variants may have a synergistic effect leading to a polyposis predisposition in high division tissues such as the colon epithelium. To check this hypothesis, somatic mutation screening and RNA expression analyses were performed in adenomas and CRC from the carrier. The analysis of somatic mutations showed a tendency to C > T changes  in the polyposis predisposition of this patient and we considered the possibility that POLE:c.141delG p.Phe48Leufs*6 could confer the adenoma predisposition by itself. Only 0.005% of POLE coding variants described in gnomAD are truncating (frameshift or nonsense); non homozygous have been described and all truncating variants show allelic frequencies lower than 1/10000. Moreover, there are two studies in the literature describing germline frameshift variants at POLE; c.5621_5622delGT was detected in a sporadic CRC patient with a diagnosis age of 2625, and c.1370_1371delAT p.Tyr457fs*9 was later detected in an AAP patient10. In addition, as it has been mentioned above, somatic driver mutations have been recently described in POLE and POLD1 polymerase domains21.Therefore, it is plausible that es Table , althougoma Fig. , which iues Fig. . This ovPOLE variant, but not the NTHL1 one, and the other did not harbor any of the variants  and an average diagnosis age lower than the general study cohort (57.2). Other works analyzing AAP cohorts, such as GroverAPC and MUTYH. Related pathogenic mutations have not been detected in any gene. However, uncertain significance variants have been detected in all genes but MSH3. Since they are recently described genes, the identification of potential pathogenic variants and further clarification of their pathogenicity is important for the definition of the syndrome.The contribution of new predisposition genes is much smaller than that of the known genes Somatic genetic screening of affected tissues allows the detection of certain mutational signatures associated with DNA repair deficiency, helping the classification of the variants.The expected low mutation detection rate in AAP study cohort point to the necessity of stronger clinical criteria for the improvement of the diagnostic sensitivity in AAP genetic testing.POLE/POLD1 truncating mutations detected in AAP cases is very limited, due to the genetic heterogeneity of the disease, the relevance of these genes and the decreased levels of carrier’s tumor and adenoma samples shown in this work, special attention should be paid to those POLE/POLD1 truncating variants in order to determine their pathogenicity.Although the number of Summarizing, this work highlights the need of multigene panel testing in highly genetic heterogeneous syndromes such as AAP, not only to increase the cost-effectiveness and the diagnostic sensitivity of the analysis, but also to better detect other potentially pathogenic variants or other inherited forms of the disease that would not be detected by other gene directed approaches.This work is a translational study aiming to analyze the contribution of known and new described adenomatous polyposis predisposition genes and the suitability of their genetic testing in a hospital based cohort that have been referred to the genetic counseling unit. The results shown above lead to the following conclusions:MUTYH (NM_0012222.2) mutations in the Spanish population19: c.536A > G; p.(Tyr179Cys), c.1187G > A; p.(Gly396Asp), c.1227_1228dup; p.(Glu410Glyfs*43) and c.1437_1439delGGA; p.(Glu480del), by HRM and/or Sanger sequencing. The presence of biallelic MUTYH mutations was considered as an exclusion criterion, but not the presence of monoallelic MUTYH mutations. APC screening was not an inclusion criterion, but the previous detection of a pathogenic APC mutation was considered as an exclusion criterion.The inclusion criterion was the detection of between 10 and 100 adenomas in the colon and/or rectum. All the samples had been screened, at least, for the most frequent A total of 158 unrelated AAP cases was included in the study . A written informed consent was obtained from each participant. Methods were compliant with the relevant guidelines and regulations.Peripheral-blood DNA/RNA extraction was performed with the MagNA Pure Compact extractor (Roche), according to the manufacturer’s protocol. Tissue DNA/RNA  was obtained from formalin-fixed paraffin-embedded (FFPE) tissues with a purity greater than 80% as determined by an experienced pathologist. DNA extractions were performed with the QIAamp DNA FFPE Tissue kit (Qiagen N.V.) and RNA extractions with the RNAeasy FFPE kit (Qiagen N.V.). SuperScript First-Strand Synthesis System for RT-PCR (Thermo Fisher Scientific) was used to synthesize cDNA, either from blood or tissue RNA, using random hexamers and oligo-dT, according to the manufacturer’s instructions.APC, MUTYH, POLE, POLD1, NTHL1, MSH3 and AXIN2 variants in the coding regions and intron-exon boundaries through an NGS Haloplex custom panel (Agilent Technologies). Enriched libraries were obtained according to the manufacturer’s protocol, and subsequently sequenced on a MiSeq System . Data analysis and variant calling were achieved with the SureCall software (Agilent Technologies) following the recommended pipeline for Haloplex libraries. Low covered regions (read depth <50) were analyzed by HRM. CNVs analyses at APC and MUTYH loci were performed by multiplex ligation and probe amplification (MLPA) .Germline DNAs were screened for 31 and 1000 genomes project32 databases), deleterious or possible deleterious variants  were selected for validation by Sanger sequencing. MaxEnt, and human splicing finder (HSF)33 were used to predict splicing alterations, while SIFT34, Polyphen235 and MutationTaster36 predicted protein damage.All rare  <0.01 according to the gnomAD37 LOVD38, UMD39, ClinVar40) and supporting pathogenic and/or benign evidences, in accordance to the ACMG-SHERLOC criteria42.Variants were classified in five different pathogenicity classes  according to the public mutational databases  , which includes 174 relevant regions located in 26 genes involved in solid tumors. Sequencing was performed on a MiSeq System . Data analysis and variant calling were performed through the plug-in specific Amplicon DS workflow for the MiSeq Reporter Software tool . PASS filter variants, according to the default settings, were first selected. Variants that failed to pass default filters, but that were detected in both pools (i.e. showing a low coverage depth or strand bias) were manually inspected using the Integrative Genome Viewer (IGV) browser44.By single-molecule molecular inversion probe (smMIP) sequencing, two adenomas (83AD1 and 83AD4) and one adenocarcinoma (83AC1) were also investigated for the occurrence of somatic mutations in the open reading frames and hotspot regions of 57 genes involved in CRC development, as described previouslyMUTYH:c.1510_1517delinsCCAACAGCCA p.(Thr504Profs*68), three adenomas of patient 89 were analyzed for KRAS somatic mutations at codons 12 and 13 by the Therascreen KRAS RGQ PCR Kit (Qiagen N.V.), according to the manufacturer’s protocol.In order to characterize the variant NTHL1 and POLE wild type allele expression levels were evaluated in three adenomas , one adenocarcinoma (83AC1) and one healthy colon tissue (83COLON) from patient 83 and compared to healthy colon and colorectal cancer control pools (COLON and CRC). The healthy colon pool was made up of eight FFPE colon tissue-derived RNA samples from unrelated healthy subjects, while the colon cancer pool was made up of eight FFPE CRC tissue-derived RNA samples from unrelated patients. All samples were previously treated with RNase-free recombinant DNase I (Roche) and the lack of germline DNA traces was checked by specific germline and cDNA amplification (Suppl. Fig. PSMB4 was used as an endogenous gene (Suppl. Table For each of the genes to be tested, primer pairs were designed for the specific detection of the wild type allele, and 42Reclassification of variants was achieved according to the supporting pathogenic and/or benign evidences, in accordance to the ACMG-SHERLOC criteriaSupplementary information


Circadian timing of treatments can largely improve tolerability and efficacy in patients. Thus, drug metabolism and cell cycle are controlled by molecular clocks in each cell and coordinated by the core body temperature 24-hour rhythm, which is generated by the hypothalamic pacemaker. Individual circadian phase is currently estimated with questionnaire-based chronotype, center-of-rest time, dim light melatonin onset (DLMO), or timing of core body temperature (CBT) maximum (acrophase) or minimum (bathyphase).We aimed at circadian phase determination and readout during daily routines in volunteers stratified by sex and age. We measured (a) chronotype, (b) every minute (q1min) CBT using 2 electronic pills swallowed 24 hours apart, (c) DLMO through hourly salivary samples from 1800 hours to bedtime, and (d) q1min accelerations and surface temperature at anterior chest level for 7 days, using a teletransmitting sensor. Circadian phases were computed using cosinor and hidden Markov modeling. Multivariate regression identified the combination of biomarkers that best predicted core temperature circadian bathyphase.R2 = 0.637).Among the 33 participants, individual circadian phases were spread over 5 hours, 10 minutes (DLMO); 7 hours (CBT bathyphase); and 9 hours, 10 minutes (surface temperature acrophase). CBT bathyphase was accurately predicted, i.e., with an error less than 1 hour for 78.8% of the subjects, using a new digital health algorithm (INTime), combining time-invariant sex and chronotype score with computed center-of-rest time and surface temperature bathyphase (adjusted INTime provided a continuous and reliable circadian phase estimate in real time. This model helps integrate circadian clocks into precision medicine and will enable treatment timing personalization following further validation.Medical Research Council, United Kingdom; AP-HP Foundation; and INSERM.  The prediction of core body temperature bathyphase enables the personalization of treatment timing, thus reducing the risk of adverse events and improving therapeutic outcomes. The discovery of the molecular mechanisms of circadian clocks has highlighted a new potential for improving human health through the translation of circadian timing concepts to medical practice –3. In maThus, it is necessary to reliably determine the circadian phase in real time for each patient, using a noninvasive and simple method, to fulfill the promises resulting from the discovery of circadian clock mechanisms for precision medicine. Novel diagnostic tools have to be developed that aim both at the prevention of circadian disorders, which can lead to chronic diseases or their exacerbation, and at the personalization of clock-based therapies for cancers and other chronic diseases.Toward this goal, the current study aimed at the continuous and remote determination of the individual subject’s bathyphase (timing of the computed daily nadir) of the overt 24-hour rhythm in core body temperature. New digital health methods and an algorithm were designed here for computing internal circadian phase (INTime) in people whose circadian rhythms were telemonitored in real time during their daily routine.https://doi.org/10.1172/jci.insight.130423DS1). The majority of participants had no ongoing medical condition and were not taking any medication. Oral contraceptive pills or intrauterine systems were used by 39% of the female participants.Of the 37 recruited participants, 33 provided valid data, including 15 males and 18 females, aged 21–78 years, with a similar distribution according to age . Thus, we used the estimated threshold method to compute the DLMOs of the 24 subjects. The median clock hour of melatonin secretion onset occurred at 2050 hours with an IQR of 2001 to 2119 hours and individual values spread over 5 hours, 10 minutes . Salivary melatonin data were available for computing DLMO using a threshold based on individual baseline values for 12 participants (40%) . The est minutes .Overall, core body temperature time series were provided by both e-Celsius pills in each subject for a median time span of 2.9 days , ranging from 1.3 up to 14.4 days according to individual gastrointestinal transit. Each of the 66 pills ingested by the 33 participants provided temperature time series over durations ranging from 0.2 to 13.4 days . There was an overlap of 24 hours or more for the records by the first and second pill in 13 subjects. Raw temperature data from both pills were correlated within each of these 13 participants, with a median Pearson’s correlation coefficient of 0.86  that was highest with a time lag of –2 minutes.Our cosinor analysis revealed that most individuals displayed a strong 24-hour rhythmic pattern occasionally with an additional prominent 12-hour component . We founRest-activity and temperature time series from the chest surface sensor were available for the 33 participants, for a median duration of 7.0 days . Large intersubject variations were obvious . Thus, mChest surface temperature lowest daily values in fitted curves from individual participants ranged from 32.1°C to 36.4°C and highest daily values from 34.5°C to 36.8°C.Rest-activity time series displayed regular 24-hour patterns that were highly reproducible from one day to the next in all the subjects, as indicated with prominent 24-hour periods according to spectral analyses . HarmoniSpectral analyses , 28 of ct test and pairwise Spearman’s correlation (P > 0.10). In contrast, circadian phase estimates were correlated to some extent  and bathyphase  , chest surface temperature acrophase , and core temperature bathyphase . The center-of-rest time was further correlated with both chest surface and core temperature acrophases  and core temperature bathyphase . Stepwise model selection identified the “best” regression model for predicting core temperature bathyphase, with an adjusted R2 of 0.637. The resulting model named “INTime” predicted core temperature bathyphase using the covariates sex (P < 0.001) and chronotype score (P = 0.009) as well as 2 computed phase indicators from the chest sensor data, namely the center-of-rest time (P = 0.033) and chest surface temperature bathyphase (P = 0.063) by means of the following estimated equation: core temperature bathyphase = (1.33 × sex) – (0.058 × chronotype score) + (0.472 × center-of-rest time) – (0.145 × chest temperature bathyphase), with sex being coded as 1 for male and 0 for female and phases in hours and decimal hours.No statistically significant correlation was found between sex, age, BMI, or concurrent treatment, on the one hand, and the various phase indicators, on the other hand, according to 2-sample e extent . The DLM = 0.09) . ChronotThe accuracy of the predicted core temperature bathyphase  was compIntersubject differences in chronotype make it crucial to perform circadian rhythm measurements without interfering with the daily life of people, to successfully translate and broadly apply circadian clock concepts to precision medicine. The current study represents an important step toward such a goal because it revealed interindividual differences by 7 hours for the bathyphase of core body temperature; by 5 hours, 10 minutes for DLMO; by 5 hours, 15 minutes for center-of-rest time; and by 9 hours, 10 minutes for the acrophase of chest surface temperature, thus highlighting large intersubject variability for these distinct and correlated estimates of circadian phase. The endogenous circadian rhythms in core body temperature, as continuously recorded using a rectal probe , and thon. By applying 1000 Monte Carlo simulation trials, we found that n = 600 and n = 1000 samples would be required to stabilize the INTime model fit so that the corresponding 90% and 95% CIs of the adjusted R2 were less than 10% of the given value of 0.637.Both the limited sample size available for DLMO estimations and the weak correlations between DLMO and other timing indicators precluded any attempt toward the search for a prediction model of DLMO. Moreover, the ability to reset most peripheral clocks with physiological temperature cycles but not with melatonin supported a potential key role of this rhythm for the biomedical applications of circadian clocks. The limitations of our study involve the measurement of core body temperature within various segments of the gastrointestinal tract and the lack of a validation sample of the INTime model. Previous studies have shown that the circadian patterns in body temperature measurements were very similar if taken from gut using an ingested pill or from the rectum using a dedicated probe , thus suOur findings have a major potential impact for the reduction of severe adverse events from treatments, whose reduction represents a critical challenge for improving patient quality of life, treatment compliance, treatment efficacy, and human health care cost burden. As an example, a 10.8-fold increase in the yearly rate of emergency visits for cancer treatment–related toxicities has been documented over 10 years in a large US study, where 91% of the emergency visits translated into emergency admissions, and 4.9% of deaths, resulting in related costs of billions of US dollars .In conclusion, using a teletransmitting dual-function chest sensor and INTime, treatment timing can be personalized both between and within patients, thus potentially reducing adverse events and improving therapeutic outcomes. Such personalized chronotherapy deserves prospective testing and could help invert the steadily rising economic burden of treatment morbidities in cancer and chronic diseases.The study aimed at (a) the estimation of the internal circadian phase during daily routines, a process that usually requires a constraining circadian physiology protocol in the laboratory , 33, andWe aimed to recruit 30 adult volunteers stratified by sex and age above or below 40 years with valid data.Eligibility criteria included the ability to work or to perform usual activities and to be aged 18 years or more. Exclusion criteria involved any uncontrolled pathological or psychological condition; any known gastrointestinal disease; any ongoing treatment with glucocorticosteroids, melatonin agonists or antagonists, lithium, or analgesic; any contraindication to the use of electronic devices; and night shift work or crossing of more than 3 time zones within the past 4 weeks. Volunteers were recruited locally through flyers and advertisements in newsletters and local journals. The study participants were asked not to change their free-living daily schedule throughout the study, except on the evening when they were to collect 6 hourly samples at home in dim light starting at 1800 hours until usual bedtime.Main characteristics of the subjects, including sex, birth date, marital status, professional activity, and past and current illnesses and treatments, were recorded upon study entry. Chest surface temperature, activity, and 3D orientation were recorded every minute for 1 week using the PiCADo mobile eHealth platform . These 3Saliva was self-collected by the participants using saliva collection aids  and 2-mL micro tubes (SARSTEDT AG & Co.). Participants were asked to collect 5 hourly samples at home during an evening in dim light starting at 1800 hours and a sixth one at 2300 hours or before retiring, whichever came first. Dim light conditions were verified using a wrist actigraph , with all subjects being reminded not to occlude the light sensor with sleeves. A salivary sample was considered invalid for melatonin determination if light intensities greater than 50 lux  had beenCore body temperature was measured using an electronic, ingestible pill . Participants were asked to ingest 1 such pill in the morning for 2 consecutive days. Data were transmitted via radio frequency to a dedicated monitor . Data were transferred from the monitor to the computer of the biomedical engineer after both pills had been eliminated through the stools. The abnormally low or high core body temperature values in the first few hours of recording were deleted because they were typically due to the temperature of food or drink ingestion. Data from the first ingested pill were used until pill elimination in the feces. Data from the second pill were used thereafter to obtain a complete time series. Participants provided a detailed diary with time of awakening and retiring, mealtimes, intense activity times, and medication times (if any).Chronotypes were determined using the largely validated morningness-eveningness self-assessment questionnaire .Teletransmitted chest sensor data were stored on the server based on HL7 standards . Data were downloaded from the server to the computer of the biomedical engineer only. Anonymized data were saved on a secure storage server according to the national Data Protection and Freedom of Information Acts guidance. Data transmission was inspected at least twice a week during the monitoring sessions to ensure adequate functioning.e-Celsius temperature data from the ingestible pills were received on the BodyCAP monitor. Similarly, after retrieval of the monitor from the subjects, data were downloaded and saved on a secure storage server according to the national Data Protection and Freedom of Information Acts guidance.DLMO is commonly computed as the time when melatonin concentration in plasma or saliva exceeds a threshold computed as the mean of 3 consecutive daytime values before rise plus twice the standard deviation of these 3 points . For thoT1 = 12 hours and T2 = 24 hours to describe the average day oscillation of both chest surface and core body temperatures based on prior evidence y(t) is the temperature at time t; M is the mesor (mean level of the fitted cosine function); 1a and 2a and 1b and 2b are the coefficients of the cosinor model, and e(t) is the error. Given the periods T1 and T2, the coefficients were estimated by least-squares linear regression. We report the overall acrophase maxθ̂ , i.e., time of maximal value in the fitted values ŷ(t), and the overall bathyphase minθ̂ , i.e., time of minimal value in ŷ(t). Note that for core body temperature, we considered mainly bathyphase because it could be identified with a better precision than acrophase in most individuals. Ninety percent CIs for maxθ̂  and minθ̂  were evaluated and reported by applying n = 1000 bootstrap trials  was computed to study the reliability of the prediction. A prediction accuracy of less than 1 hour was considered precise enough for clinical applications.Significance of explanatory variables was also tested by 2-tailed https://github.com/huang1010/JCI-insightR-codes to obtain the datasets corresponding to the salivary melatonin profiles, the core body temperature patterns, and the rest activity and chest surface temperature patterns displayed in The protocol and subsequent amendments were approved by the Ethical Committee of Warwick University (REGO-2017-2055). The study was conducted according to the Helsinki Declaration . The subThe study was co-conceived by SK, MB, and FL. Funding resources were obtained mainly by FL, and the study management was carried out by SK and MB. Technical supervision was performed by SK and MB. Methods were designed by SK, MB, QH, BF, and FL. SK and MB included participants in the study. Data were collected and curated by SK and MB. Statistical methods development and programming were performed by QH. Data analysis was performed by SK and QH. Data interpretation involved SK, MB, QH, BF, and FL. The manuscript drafting and its editing and final approval involved SK, MB, QH, BF, and FL.