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Genetic variants affect diurnal glucose levels throughout the day.

ABSTRACT: Circadian rhythms not only coordinate the timing of wake and sleep but also regulate homeostasis within the body, including glucose metabolism. However, the genetic variants that contribute to temporal control of glucose levels have not been previously examined. Using data from 420,000 individuals from the UK Biobank and replicating our findings in 100,000 individuals from the Estonian Biobank, we show that diurnal serum glucose is under genetic control. We discover a robust temporal association of glucose levels at the Melatonin receptor 1B (MTNR1B) (rs10830963, P = 1e-22) and a canonical circadian pacemaker gene Cryptochrome 2 (CRY2) loci (rs12419690, P = 1e-16). Furthermore, we show that sleep modulates serum glucose levels and the genetic variants have a separate mechanism of diurnal control. Finally, we show that these variants independently modulate risk of type 2 diabetes. Our findings, together with earlier genetic and epidemiological evidence, show a clear connection between sleep and metabolism and highlight variation at MTNR1B and CRY2 as temporal regulators for glucose levels.

SUBMITTER: Sinnott-Armstrong N

PROVIDER: S-EPMC11291026 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

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Genetic variants affect diurnal glucose levels throughout the day.

Sinnott-Armstrong Nasa N Strausz Satu S Urpa Lea L Abner Erik E Valliere Jesse J Palta Priit P Dashti Hassan S HS Daly Mark M Pritchard Jonathan K JK Saxena Richa R Jones Samuel E SE Ollila Hanna M HM

bioRxiv : the preprint server for biology 20240723

Circadian rhythms not only coordinate the timing of wake and sleep but also regulate homeostasis within the body, including glucose metabolism. However, the genetic variants that contribute to temporal control of glucose levels have not been previously examined. Using data from 420,000 individuals from the UK Biobank and replicating our findings in 100,000 individuals from the Estonian Biobank, we show that diurnal serum glucose is under genetic control. We discover a robust temporal association ...[more]

PMID: 39091879

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Project description:BackgroundRNA-sequencing (RNA-seq) is a powerful technique for the identification of genetic variants that affect gene-expression levels, either through expression quantitative trait locus (eQTL) mapping or through allele-specific expression (ASE) analysis. Given increasing numbers of RNA-seq samples in the public domain, we here studied to what extent eQTLs and ASE effects can be identified when using public RNA-seq data while deriving the genotypes from the RNA-sequencing reads themselves.MethodsWe downloaded the raw reads for all available human RNA-seq datasets. Using these reads we performed gene expression quantification. All samples were jointly normalized and subjected to a strict quality control. We also derived genotypes using the RNA-seq reads and used imputation to infer non-coding variants. This allowed us to perform eQTL mapping and ASE analyses jointly on all samples that passed quality control. Our results were validated using samples for which DNA-seq genotypes were available.Results4,978 public human RNA-seq runs, representing many different tissues and cell-types, passed quality control. Even though these data originated from many different laboratories, samples reflecting the same cell type clustered together, suggesting that technical biases due to different sequencing protocols are limited. In a joint analysis on the 1,262 samples with high quality genotypes, we identified cis-eQTLs effects for 8,034 unique genes (at a false discovery rate ≤0.05). eQTL mapping on individual tissues revealed that a limited number of samples already suffice to identify tissue-specific eQTLs for known disease-associated genetic variants. Additionally, we observed strong ASE effects for 34 rare pathogenic variants, corroborating previously observed effects on the corresponding protein levels.ConclusionsBy deriving and imputing genotypes from RNA-seq data, it is possible to identify both eQTLs and ASE effects. Given the exponential growth of the number of publicly available RNA-seq samples, we expect this approach will become especially relevant for studying the effects of tissue-specific and rare pathogenic genetic variants to aid clinical interpretation of exome and genome sequencing.

Project description:BackgroundTrainability in dogs is affected by learning aptitude and memory capacity. While this trait has a heritable basis in canines, the specific genetic loci responsible for it remain unknown. Our previous results suggested that the BDNF, CCK and TAC1 genes are associated with learning and memory in canines. Experimental validation is crucial to confirm the effects of these candidate genes on trainability. Understanding the genetic foundation of this trait would offer insight into the inheritance pattern of complex behavioural characteristics.ObjectiveThis study aimed to assess the genetic variations within candidate genes and explore their potential associations with behavioural phenotypes in dogs.MethodsThe behavioural characteristics of 123 male Belgian Malinois dogs were assessed using a customised questionnaire. Target regions of candidate genes were screened for genetic variation by single-strand conformational polymorphism (SSCP). Following that, SSCP banding patterns were sequenced, and putative transcription factor binding sites were predicted using bioinformatics tools. Quantitative association analysis between identified genetic variants and behavioural trait scores was performed using the general linear model (GLM).ResultsSequencing the coding and flanking regions revealed three mutations (c.-89C>T, c.-162G>C and c.*33T>A) in the dog TAC1 gene. Bioinformatics analysis predicted two single nucleotide polymorphisms (SNPs) were located within the putative TAC1 promoter and could disrupt transcription factor binding sites. Statistical tests revealed that the c.-89C>T was significantly associated with excitability (p < 0.01), while the c.-162G>C was significantly associated with trainability level (p < 0.05).ConclusionIn summary, we identified two regulatory SNPs in the 5'-UTR promoter region of the TAC1 gene that are associated with excitability and trainability in Belgian Malinois dogs. These genetic variations have the potential to alter the binding sites of transcription factors NRF1 and OTX1, consequently influencing TAC1 expression and related behavioural characteristics. Our findings implicate TAC1 polymorphisms as candidates influencing breed-specific behavioural characteristics in canines. Further studies on diverse breeds of dogs are necessary to validate these SNPs' effects.

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Genetic variants affect diurnal glucose levels throughout the day.

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Genetic variants affect diurnal glucose levels throughout the day.

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