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Integrative Identification of Genetic Loci Jointly Influencing Diabetes-Related Traits and Sleep Traits of Insomnia, Sleep Duration, and Chronotypes.

ABSTRACT: Accumulating evidence suggests a relationship between type 2 diabetes mellitus and sleep problems. A comprehensive study is needed to decipher whether shared polygenic risk variants exist between diabetic traits and sleep traits. We integrated summary statistics from different genome-wide association studies and investigated overlap in single-nucleotide polymorphisms (SNPs) associated with diabetes-related traits (type 2 diabetes, fasting glucose, fasting insulin, and glycated hemoglobin) and sleep traits (insomnia symptoms, sleep duration, and chronotype) using a conditional/conjunctional false discovery rate approach. Pleiotropic genes were further evaluated for differential expression analysis, and we assessed their expression pattern effects on type 2 diabetes by Mendelian randomization (MR) analysis. We observed extensive polygenic pleiotropy between diabetic traits and sleep traits. Fifty-eight independent genetic loci jointly influenced the risk of type 2 diabetes and the sleep traits of insomnia, sleep duration, and chronotype. The strongest shared locus between type 2 diabetes and sleep straits was FTO (lead SNP rs8047587). Type 2 diabetes (z score, 16.19; P = 6.29 × 10-59) and two sleep traits, sleep duration (z score, -6.66; P = 2.66 × 10-11) and chronotype (z score, 7.42; P = 1.19 × 10-13), were shared. Two of the pleiotropic genes, ENSA and PMPCA, were validated to be differentially expressed in type 2 diabetes, and PMPCA showed a slight protective effect on type 2 diabetes in MR analysis. Our study provided evidence for the polygenic overlap between diabetic traits and sleep traits, of which the expression of PMPCA may play a crucial role and provide support of the hazardous effect of being an "evening" person on diabetes risk.

SUBMITTER: Ma Y

PROVIDER: S-EPMC8962243 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Integrative Identification of Genetic Loci Jointly Influencing Diabetes-Related Traits and Sleep Traits of Insomnia, Sleep Duration, and Chronotypes.

Ma Yujia Y Zhou Zechen Z Li Xiaoyi X Yan Zeyu Z Ding Kexin K Xiao Han H Wu Yiqun Y Wu Tao T Chen Dafang D

Biomedicines 20220202 2

Accumulating evidence suggests a relationship between type 2 diabetes mellitus and sleep problems. A comprehensive study is needed to decipher whether shared polygenic risk variants exist between diabetic traits and sleep traits.<h4>Methods</h4>We integrated summary statistics from different genome-wide association studies and investigated overlap in single-nucleotide polymorphisms (SNPs) associated with diabetes-related traits (type 2 diabetes, fasting glucose, fasting insulin, and glycated hem ...[more]

PMID: 35203577

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Project description:BackgroundComorbidities of coronavirus disease 2019 (COVID-19)/coronary heart disease (CHD) pose great threats to disease outcomes, yet little is known about their shared pathology. The study aimed to examine whether comorbidities of COVID-19/CHD involved shared genetic pathology, as well as to clarify the shared genetic variants predisposing risks common to COVID-19 severity and CHD risks.MethodsBy leveraging publicly available summary statistics, we assessed the genetically determined causality between COVID-19 and CHD with bidirectional Mendelian randomization. To further quantify the causality contributed by shared genetic variants, we interrogated their genetic correlation with the linkage disequilibrium score regression method. Bayesian colocalization analysis coupled with conditional/conjunctional false discovery rate analysis was applied to decipher the shared causal single nucleotide polymorphisms (SNPs).FindingsBriefly, we observed that the incident CHD risks post COVID-19 infection were partially determined by shared genetic variants. The shared genetic variants contributed to the causality at a proportion of 0.18 (95% CI 0.18-0.19) to 0.23 (95% CI 0.23-0.24). The SNP (rs10490770) located near LZTFL1 suggested direct causality (SNPs → COVID-19 → CHD), and SNPs in ABO (rs579459, rs495828), ILRUN(rs2744961), and CACFD1(rs4962153, rs3094379) may simultaneously influence COVID-19 severity and CHD risks.InterpretationFive SNPs located near LZTFL1 (rs10490770), ABO (rs579459, rs495828), ILRUN (rs2744961), and CACFD1 (rs4962153, rs3094379) may simultaneously influence their risks. The current study suggested that there may be shared mechanisms predisposing to both COVID-19 severity and CHD risks. Genetic predisposition to COVID-19 is a causal risk factor for CHD, supporting that reducing the COVID-19 infection risk or alleviating COVID-19 severity among those with specific genotypes might reduce their subsequent CHD adverse outcomes. Meanwhile, the shared genetic variants identified may be of clinical implications for identifying the target population who are more vulnerable to adverse CHD outcomes post COVID-19 and may also advance treatments of 'Long COVID-19.'

Project description:ImportanceSchizophrenia is associated with widespread cognitive impairments. Although cognitive deficits are one of the factors most strongly associated with functional outcome in schizophrenia, current treatment strategies largely fail to ameliorate these impairments. To develop more efficient treatment strategies in patients with schizophrenia, a better understanding of the pathogenesis of these cognitive deficits is needed. Accumulating evidence indicates that genetic risk of schizophrenia may contribute to cognitive dysfunction.ObjectiveTo identify genomic regions jointly influencing schizophrenia and the cognitive domains of reaction time and verbal-numerical reasoning, as well as general cognitive function, a phenotype that captures the shared variation in performance across cognitive domains.Design, setting, and participantsCombining data from genome-wide association studies from multiple phenotypes using conditional false discovery rate analysis provides increased power to discover genetic variants and could elucidate shared molecular genetic mechanisms. Data from the following genome-wide association studies, published from July 24, 2014, to January 17, 2017, were combined: schizophrenia in the Psychiatric Genomics Consortium cohort (n = 79 757 [cases, 34 486; controls, 45 271]); verbal-numerical reasoning (n = 36 035) and reaction time (n = 111 483) in the UK Biobank cohort; and general cognitive function in CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) (n = 53 949) and COGENT (Cognitive Genomics Consortium) (n = 27 888).Main outcomes and measuresGenetic loci identified by conditional false discovery rate analysis. Brain messenger RNA expression and brain expression quantitative trait locus functionality were determined.ResultsAmong the participants in the genome-wide association studies, 21 loci jointly influencing schizophrenia and cognitive traits were identified: 2 loci shared between schizophrenia and verbal-numerical reasoning, 6 loci shared between schizophrenia and reaction time, and 14 loci shared between schizophrenia and general cognitive function. One locus was shared between schizophrenia and 2 cognitive traits and represented the strongest shared signal detected (nearest gene TCF20; chromosome 22q13.2), and was shared between schizophrenia (z score, 5.01; P = 5.53 × 10-7), general cognitive function (z score, -4.43; P = 9.42 × 10-6), and verbal-numerical reasoning (z score, -5.43; P = 5.64 × 10-8). For 18 loci, schizophrenia risk alleles were associated with poorer cognitive performance. The implicated genes are expressed in the developmental and adult human brain. Replicable expression quantitative trait locus functionality was identified for 4 loci in the adult human brain.Conclusions and relevanceThe discovered loci improve the understanding of the common genetic basis underlying schizophrenia and cognitive function, suggesting novel molecular genetic mechanisms.

Project description:ObjectivesExtensive researches highlight the detrimental impact of sleep disorders such as insomnia and insufficient sleep duration on kidney function. However, establishing a clear causal relationship between insomnia, sleep duration, and kidney function remains challenging. This study aims to estimate this relationship using Mendelian randomization (MR).MethodsIndependent genetic variants strongly associated with insomnia (N = 462,341) and sleep duration (N = 460,099) were selected as instrumental variables from corresponding genome-wide association studies (GWAS). Kidney function parameters, including serum creatinine, estimated glomerular filtration rate by cystatin C (eGFRcys), acute renal failure (ARF), chronic renal failure (CRF), kidney injury molecule-1, neutrophil gelatinase associated lipocalin, microalbuminuria, cystatin C, and β2 microglobulin, were derived from GWAS databases. A two-sample MR study was conducted to assess the causal relationship between sleep disorders and kidney function, and multivariable MR was used to identify potential mediators. The inverse-variance weighted was used as the primary estimate.ResultsMR analysis found robust evidence indicating that insomnia and short sleep duration were associated with an increased risk of elevated serum creatinine, regardless of adjusting for obesity. Causal links between sleep duration and eGFRcys or cystatin C were also identified. While genetically predicted insomnia and sleep duration were found to potentially impact ARF, CRF, microalbuminuria, and β2 microglobulin, the p-values in multivariable MR analysis became nonsignificant. No pleiotropy was detected.ConclusionsThis study demonstrates a causal impact of insomnia on the risk of elevated serum creatinine and a positive effect of sleep duration on serum creatinine, eGFRcys, and cystatin C. Our findings also suggest their potential indirect effects on ARF, CRF, microalbuminuria, and β2 microglobulin mediated by obesity.

Project description:This study examined whether individuals with insomnia and objective short sleep duration <6 h, a subgroup with greater risks of adverse health outcomes, differ in their response to cognitive-behavioral therapy for insomnia (CBT-I) when compared to individuals with insomnia and normal sleep duration ≥6 h. Secondary analyses of a randomized, clinical trial with 60 adult participants (n = 31 women) from a single academic medical center. Outpatient treatment lasted 8 weeks, with a final follow-up conducted at 6 months. Mixed-effects models controlling for age, sex, CBT-I treatment group assignment, and treatment provider examined sleep parameters gathered via actigraphy, sleep diaries, and an Insomnia Symptom Questionnaire (ISQ) across the treatment and follow-up period. Six months post-CBT-I treatment, individuals with insomnia and normal sleep duration ≥6 h fared significantly better on clinical improvement milestones than did those with insomnia and short sleep duration <6 h. Specifically, individuals with insomnia and normal sleep duration had significantly higher insomnia remission (ISQ < 36.5; χ2[1, N = 60] = 44.72, p < .0001), more normative sleep efficiency (SE) on actigraphy (SE > 80%; χ2[1, N = 60] = 21, p < .0001), normal levels of middle of the night wake after sleep onset (MWASO) <31 minutes (χ2[1, N = 60] = 37.85, p < .0001), and a >50% decline in MWASO (χ2[1, N = 60] = 60, p < .0001) compared to individuals with insomnia and short sleep duration. Additionally, those with insomnia and normal sleep duration had more success decreasing their total wake time (TWT) at the 6-month follow-up compared to those with insomnia and short sleep duration (χ2[2, N = 60] = 44.1, p < .0001). Receiver-operating characteristic curve analysis found that using a 6-h cutoff with actigraphy provided a 95.7% sensitivity and 91.9% specificity for determining insomnia remission, with the area under the curve = 0.986. Findings suggest that individuals with insomnia and objective short sleep duration <6 h are significantly less responsive to CBT-I than those with insomnia and normal sleep duration ≥6 h. Using an actigraphy TST cutoff of 6 hours to classify sleep duration groups was highly accurate and provided good discriminant value for determining insomnia remission.

Dataset Information

Integrative Identification of Genetic Loci Jointly Influencing Diabetes-Related Traits and Sleep Traits of Insomnia, Sleep Duration, and Chronotypes.

Publications

Integrative Identification of Genetic Loci Jointly Influencing Diabetes-Related Traits and Sleep Traits of Insomnia, Sleep Duration, and Chronotypes.

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