Ketogenic diet combined with intermittent fasting: an option for type 2 diabetes remission?

With increasing attention to diabetes remission, various special dietary patterns have been found to be effective in achieving diabetes remission. The effect of a single dietary pattern on lowering blood glucose is clear, but studies on the synergistic effects of different dietary patterns are limited. This article describes the types of intermittent fasting and ketogenic diets, potential mechanisms, contraindications of combination diets, recommendations for combination diets, and their health outcomes. This paper aims to illustrate the evidence for intermittent fasting combined with a ketogenic diet on outcomes of diabetes remission and effect on blood glucose control. Knowledge of these findings can help doctors and patients determine dietary patterns for achieving diabetes remission and understanding their application.

Clinical characteristics and acute complication of COVID-19 patients with diabetes: a multicenter, retrospective study in Southern China.

Aims: This study aims to describe the clinical characteristics, laboratory data and complications of hospitalized COVID-19 patients with type 2 diabetes mellitus (T2DM) since epidemic prevention and control optimization was adjusted in December 2022 in China. Methods: This retrospective multicenter study included 298 patients with confirmed type 2 diabetes mellitus with or without COVID-19. We collected data from the first wave of the pandemic in The Fifth Affiliated Hospital of Guangzhou Medical University, Loudi Central Hospital and The First People's Hospital of Xiangtan from December 1, 2022 to February 1, 2023. We extracted baseline data, clinical symptoms, acute complications, laboratory findings, treatment and outcome data of each patient from electronic medical records. Results: For among 298 hospitalized patients with type 2 diabetes, 136 (45.6%) were COVID-19 uninfected, and 162 (54.4%) were COVID-19 infected. We found that the incidence of cough, fatigue, fever, muscle soreness, sore throat, shortness of breath, hyposmia, hypogeusia and polyphagia (all p<0.01) were significantly higher in the exposure group. They showed higher levels of ketone (p=0.04), creatinine (p<0.01), blood potassium (p=0.01) and more diabetic ketoacidosis (p<0.01). Patients with COVID-19 less use of metformin (p<0.01), thiazolidinediones (p<0.01) and SGLT2 (p<0.01) compared with patients without COVID-19. Conclusion: COVID-19 patients with diabetes showed more severe respiratory and constitutional symptoms and an increased proportion of hyposmia and hypogeusia. Moreover, COVID-19 patients with diabetes have a higher incidence of acute complications, are more prone to worsening renal function, and are more cautious about the use of antidiabetic drugs.

Exploring the novel SNPs in neuroticism and birth weight based on GWAS datasets.

OBJECTIVES: Epidemiological studies have confirmed that low birth weight (BW) is related to neuroticism and they may have a common genetic mechanism based on phenotypic correlation research. We conducted our study on a European population with 159,208 neuroticism and 289,142 birth weight samples. In this study, we aimed to identify new neuroticism single nucleotide polymorphisms (SNPs) and pleiotropic SNPs associated with neuroticism and BW and to provide more theoretical basis for the pathogenesis of the disease. METHODS: We estimated the pleiotropic enrichment between neuroticism and BW in two independent Genome-wide association studies (GWAS) when the statistical thresholds were Conditional False Discovery Rate (cFDR) < 0.01 and Conjunctional Conditional False Discovery Rate (ccFDR) < 0.05. We performed gene annotation and gene functional analysis on the selected significant SNPs to determine the biological role of gene function and pathogenesis. Two-sample Mendelian Randomization (TSMR) analysis was performed to explore the causal relationship between the neuroticism and BW. RESULTS: The conditional quantile-quantile plots (Q-Q plot) indicated that neuroticism and BW have strong genetic pleiotropy enrichment trends. With the threshold of cFDR < 0.001, we identified 126 SNPs related to neuroticism and 172 SNPs related to BW. With the threshold of ccFDR < 0.05, we identified 62 SNPs related to both neuroticism and BW. Among these SNPs, rs8039305 and rs35755513 have eQTL (expressed quantitative trait loci) and meQTL (methylation quantitative trait loci) effects simultaneously. Through GO enrichment analysis we also found that the two pathways of positive regulation of "mesenchymal cell proliferation" and "DNA-binding transcription factor activity" were significantly enriched in neuroticism and BW. Mendelian randomization analysis results indicate that there is no obvious causal relationship between neuroticism and birth weight. CONCLUSION: We found 126 SNPs related to neuroticism, 172 SNPs related to BW and 62 SNPs associated with both neuroticism and BW, which provided a theoretical basis for their genetic mechanism and novel potential targets for treatment/intervention development.

Comparative efficiency and safety of insulin degludec/aspart with insulin glargine in type 2 diabetes: a meta-analysis of randomized controlled trials.

Recent studies have found compared with insulin glargine (IGlar), insulin degludec/aspart (IDeg/Asp) may provide adequate glycemic control and prevent hypoglycemia events in type 2 diabetes mellitus (T2DM). Consequently, we performed a meta-analysis to appraise and compare the efficiency and safety of IDeg/Asp and IGlar in the treatment of T2DM. We sought the databases including PubMed, Embase, Scopus, Cochrane library to confirm related articles which inspected the effect of IDeg/Asp versus IGlar for the treatment of T2DM until May 2021. Finally, six randomized controlled trials (RCTs) of 1,346 patients were included. The results showed that IDeg/Asp significantly decreased the mean hemoglobin A1c (HbA1c) level but was prone to serious adverse events, and IGlar increased the nocturnal confirmed hypoglycemia events. Besides, there were no significant changes in other indicators, including mean fasting plasma glucose (FPG) level, nine-point self-measured plasma glucose (SMPG) level, and adverse events. What's more, we found that there was no significant difference in the occurrence of hypoglycemia overall, but our subgroup analysis of confirmed hypoglycemia revealed the population in this subgroup (duration of diabetes ≤11 years) might has its particularity effecting the hypoglycemia outcome. Concerning efficiency, IDeg/Asp may have advantages in controlling the mean HbA1c level. Regarding safety, IGlar might increase the risk of nocturnal confirmed hypoglycemia. Further evidence is needed to compare better the efficiency and safety of IDeg/Asp versus IGlar therapy.

Enhanced Identification of Novel Potential Variants for Appendicular Lean Mass by Leveraging Pleiotropy With Bone Mineral Density.

Strong relationships have been found between appendicular lean mass (ALM) and bone mineral density (BMD). It may be due to a shared genetic basis, termed pleiotropy. By leveraging the pleiotropy with BMD, the aim of this study was to detect more potential genetic variants for ALM. Using the conditional false discovery rate (cFDR) methodology, a combined analysis of the summary statistics of two large independent genome wide association studies (GWAS) of ALM (n = 73,420) and BMD (n = 10,414) was conducted. Strong pleiotropic enrichment and 26 novel potential pleiotropic SNPs were found for ALM and BMD. We identified 156 SNPs for ALM (cFDR <0.05), of which 74 were replicates of previous GWASs and 82 were novel SNPs potentially-associated with ALM. Eleven genes annotated by 31 novel SNPs (13 pleiotropic and 18 ALM specific) were partially validated in a gene expression assay. Functional enrichment analysis indicated that genes corresponding to the novel potential SNPs were enriched in GO terms and/or KEGG pathways that played important roles in muscle development and/or BMD metabolism (adjP <0.05). In protein-protein interaction analysis, rich interactions were demonstrated among the proteins produced by the corresponding genes. In conclusion, the present study, as in other recent studies we have conducted, demonstrated superior efficiency and reliability of the cFDR methodology for enhanced detection of trait-associated genetic variants. Our findings shed novel insight into the genetic variability of ALM in addition to the shared genetic basis underlying ALM and BMD.

Identification of novel functional CpG-SNPs associated with Type 2 diabetes and birth weight.

Genome-wide association studies (GWASs) have identified hundreds of genetic loci for type 2 diabetes (T2D) and birth weight (BW); however, a large proportion of the total trait heritability remains unexplained. The previous studies were generally focused on individual traits and largely failed to identify the majority of the variants that play key functional roles in the etiology of the disease. Here, we aim to identify novel functional loci for T2D, BW and the pleiotropic variants shared between them by performing a targeted conditional false discovery rate (cFDR) analysis that integrates two independent GWASs with summary statistics for T2D (n = 26,676 cases and 132,532 controls) and BW (n = 153,781) which entails greater statistical power than individual trait analyses. In this analysis, we considered CpG-SNPs, which are SNPs that may influence DNA methylation status, and are therefore considered to be functionally important. We identified 103 novel CpG-SNPs for T2D, 182 novel CpG-SNPs for BW (cFDR < 0.05), and 52 novel pleiotropic loci for both (conjunction cFDR [ccFDR] < 0.05). Among the identified novel CpG-SNPs, 33 were annotated as methylation quantitative trait loci (meQTLs) in whole blood, and 145 displayed at least some effects on meQTL, metabolic QTL (metaQTL), and/or expression QTL (eQTL). These findings may provide further insights into the shared biological mechanisms and functional genetic determinants that overlap between T2D and BW, thereby providing novel potential targets for treatment/intervention development.

Identification of novel genetic variants for type 2 diabetes, childhood obesity, and their pleiotropic loci.

Obesity has result in increased prevalence of type 2 diabetes (T2D) in children. The genetic mechanisms underlying their relationship, however, are not fully understood. Here, we aim to identify novel SNPs associated with T2D and childhood obesity (CO), especially their pleiotropic loci. We integrated the summary statistics for two independent GWASs of T2D (n = 149,821) and childhood body mass index (CBMI) (n = 35,668) using the pleiotropy-informed conditional false discovery rate (cFDR) method. By leveraging the information of different levels of association for CBMI, we observed a strong enrichment of genetic variants associated with T2D. We identified 139 T2D-associated SNPs with 125 novel ones (cFDR < 0.05). Conditioned on T2D, we identified 37 significant SNPs for CBMI (cFDR < 0.05), including 25 novel ones. The conjunctional cFDR (ccFDR) analysis showed ten novel pleiotropic loci for T2D and CBMI (ccFDR < 0.05). Interestingly, the novel SNP rs1996023 is located at protein coding gene GNPDA2 (ccFDR = 1.28E-02), which has been reported to influence the risk of T2D and CO through central nervous system. Our findings may help to explain a greater proportion of the heritability for human traits and advance the understanding of the common pathophysiology between T2D and CO.

System network analysis of genomics and transcriptomics data identified type 1 diabetes-associated pathway and genes.

Genome-wide association studies (GWASs) have discovered >50 risk loci for type 1 diabetes (T1D). However, those variations only have modest effects on the genetic risk of T1D. In recent years, accumulated studies have suggested that gene-gene interactions might explain part of the missing heritability. The purpose of our research was to identify potential and novel risk genes for T1D by systematically considering the gene-gene interactions through network analyses. We carried out a novel system network analysis of summary GWAS statistics jointly with transcriptomic gene expression data to identify some of the missing heritability for T1D using weighted gene co-expression network analysis (WGCNA). Using WGCNA, seven modules for 1852 nominally significant (P ≤ 0.05) GWAS genes were identified by analyzing microarray data for gene expression profile. One module (tagged as green module) showed significant association (P ≤ 0.05) between the module eigengenes and the trait. This module also displayed a high correlation (r = 0.45, P ≤ 0.05) between module membership (MM) and gene significant (GS), which indicated that the green module of co-expressed genes is of significant biological importance for T1D status. By further describing the module content and topology, the green module revealed a significant enrichment in the "regulation of immune response" (GO:0050776), which is a crucially important pathway in T1D development. Our findings demonstrated a module and several core genes that act as essential components in the etiology of T1D possibly via the regulation of immune response, which may enhance our fundamental knowledge of the underlying molecular mechanisms for T1D.

Identification of potential functional genes in papillary thyroid cancer by co-expression network analysis.

Interactions between multiple genes are involved in the development of complex diseases. However, there are few analyses of gene interactions associated with papillary thyroid cancer (PTC). Weighted gene co-expression network analysis (WGCNA) is a novel and powerful method that detects gene interactions according to their co-expression similarities. In the present study, WGCNA was performed in order to identify functional genes associated with PTC using R package. First, differential gene expression analysis was conducted in order to identify the differentially expressed genes (DEGs) between PTC and normal samples. Subsequently, co-expression networks of the DEGs were constructed for the two sample groups, respectively. The two networks were compared in order to identify a poorly preserved module. Concentrating on the significant module, validation analysis was performed to confirm the identified genes and combined functional enrichment analysis was conducted in order to identify more functional associations of these genes with PTC. As a result, 1062 DEGs were identified for network construction. A brown module containing 118 highly related genes was selected as it exhibited the lowest module preservation. After validation analysis, 61 genes in the module were confirmed to be associated with PTC. Following the enrichment analysis, two PTC-related pathways were identified: Wnt signal pathway and transcriptional misregulation in cancer. LRP4, KLK7, PRICKLE1, ETV4 and ETV5 were predicted to be candidate genes regulating the pathogenesis of PTC. These results provide novel insights into the etiology of PTC and the identification of potential functional genes.

Multivariate analysis of genomics data to identify potential pleiotropic genes for type 2 diabetes, obesity and dyslipidemia using Meta-CCA and gene-based approach.

Previous studies have demonstrated the genetic correlations between type 2 diabetes, obesity and dyslipidemia, and indicated that many genes have pleiotropic effects on them. However, these pleiotropic genes have not been well-defined. It is essential to identify pleiotropic genes using systematic approaches because systematically analyzing correlated traits is an effective way to enhance their statistical power. To identify potential pleiotropic genes for these three disorders, we performed a systematic analysis by incorporating GWAS (genome-wide associated study) datasets of six correlated traits related to type 2 diabetes, obesity and dyslipidemia using Meta-CCA (meta-analysis using canonical correlation analysis). Meta-CCA is an emerging method to systematically identify potential pleiotropic genes using GWAS summary statistics of multiple correlated traits. 2,720 genes were identified as significant genes after multiple testing (Bonferroni corrected p value < 0.05). Further, to refine the identified genes, we tested their relationship to the six correlated traits using VEGAS-2 (versatile gene-based association study-2). Only the genes significantly associated (Bonferroni corrected p value < 0.05) with more than one trait were kept. Finally, 25 genes (including two confirmed pleiotropic genes and eleven novel pleiotropic genes) were identified as potential pleiotropic genes. They were enriched in 5 pathways including the statin pathway and the PPAR (peroxisome proliferator-activated receptor) Alpha pathway. In summary, our study identified potential pleiotropic genes and pathways of type 2 diabetes, obesity and dyslipidemia, which may shed light on the common biological etiology and pathogenesis of these three disorders and provide promising insights for new therapies.

Linking Alzheimer's disease and type 2 diabetes: Novel shared susceptibility genes detected by cFDR approach.

BACKGROUND: Both type 2 diabetes (T2D) and Alzheimer's disease (AD) occur commonly in the aging populations and T2D has been considered as an important risk factor for AD. The heritability of both diseases is estimated to be over 50%. However, common pleiotropic single-nucleotide polymorphisms (SNPs)/loci have not been well-defined. The aim of this study is to analyze two large public accessible GWAS datasets to identify novel common genetic loci for T2D and/or AD. METHODS AND MATERIALS: The recently developed novel conditional false discovery rate (cFDR) approach was used to analyze the summary GWAS datasets from International Genomics of Alzheimer's Project (IGAP) and Diabetes Genetics Replication And Meta-analysis (DIAGRAM) to identify novel susceptibility genes for AD and T2D. RESULTS: We identified 78 SNPs (including 58 novel SNPs) that were associated with AD in Europeans conditional on T2D (cFDR<0.05). 66 T2D SNPs (including 40 novel SNPs) were identified by conditioning on SNPs association with AD (cFDR<0.05). A conjunction-cFDR (ccFDR) analysis detected 8 pleiotropic SNPs with a significance threshold of ccFDR<0.05 for both AD and T2D, of which 5 SNPs (rs6982393, rs4734295, rs7812465, rs10510109, rs2421016) were novel findings. Furthermore, among the 8 SNPs annotated at 6 different genes, 3 corresponding genes TP53INP1, TOMM40 and C8orf38 were related to mitochondrial dysfunction, critically involved in oxidative stress, which potentially contribute to the etiology of both AD and T2D. CONCLUSION: Our study provided evidence for shared genetic loci between T2D and AD in European subjects by using cFDR and ccFDR analyses. These results may provide novel insight into the etiology and potential therapeutic targets of T2D and/or AD.

Enhanced Identification of Potential Pleiotropic Genetic Variants for Bone Mineral Density and Breast Cancer.

Epidemiological and clinical evidences have shown that bone mineral density (BMD) has a close relationship with breast cancer (BC). They might potentially have a shared genetic basis. By incorporating information about these pleiotropic effects, we may be able to explore more of the traits' total heritability. We applied a recently developed conditional false discovery rate (cFDR) method to the summary statistics from two independent GWASs to identify the potential pleiotropic genetic variants for BMD and BC. By jointly analyzing two large independent GWASs of BMD and BC, we found strong pleiotropic enrichment between them and identified 102 single-nucleotide polymorphisms (SNPs) in BMD and 192 SNPs in BC with cFDR < 0.05, including 230 SNPs that might have been overlooked by the standard GWAS analysis. cFDR-significant genes were enriched in GO terms and KEGG pathways which were crucial to bone metabolism and/or BC pathology (adjP < 0.05). Some cFDR-significant genes were partially validated in the gene expressional validation assay. Strong interactions were found between proteins produced by cFDR-significant genes in the context of biological mechanism of bone metabolism and/or BC etiology. Totally, we identified 7 pleiotropic SNPs that were associated with both BMD and BC (conjunction cFDR < 0.05); CCDC170, ESR1, RANKL, CPED1, and MEOX1 might play important roles in the pleiotropy of BMD and BC. Our study highlighted the significant pleiotropy between BMD and BC and shed novel insight into trait-specific as well as the potentially shared genetic architecture for both BMD and BC.

Identification of novel genetic loci for osteoporosis and/or rheumatoid arthritis using cFDR approach.

There are co-morbidity between osteoporosis (OP) and rheumatoid arthritis (RA). Some genetic risk factors have been identified for these two phenotypes respectively in previous research; however, they accounted for only a small portion of the underlying total genetic variances. Here, we sought to identify additional common genetic loci associated with OP and/or RA. The conditional false discovery rate (cFDR) approach allows detection of additional genetic factors (those respective ones as well as common pleiotropic ones) for the two associated phenotypes. We collected and analyzed summary statistics provided by large, multi-center GWAS studies of FNK (femoral neck) BMD (a major risk factor for osteoporosis) (n = 53,236) and RA (n = 80,799). The conditional quantile-quantile (Q-Q) plots can assess the enrichment of SNPs related to FNK BMD and RA, respectively. Furthermore, we identified shared loci between FNK BMD and RA using conjunction cFDR (ccFDR). We found strong enrichment of p-values in FNK BMD when conditional Q-Q was done on RA and vice versa. We identified 30 novel OP-RA associated pleiotropic loci that have not been reported in previous OP or RA GWAS, 18 of which located in the MHC (major histocompatibility complex) region previously reported to play an important role in immune system and bone health. We identified some specific novel polygenic factors for OP and RA respectively, and identified 30 novel OP-RA associated pleiotropic loci. These discovery findings may offer novel pathobiological insights, and suggest new targets and pathways for drug development in OP and RA patients.

Genetic sharing with coronary artery disease identifies potential novel loci for bone mineral density.

Bone mineral density (BMD) is a complex trait with high missing heritability. Numerous evidences have shown that BMD variation has a relationship with coronary artery disease (CAD). This relationship may come from a common genetic basis called pleiotropy. By leveraging the pleiotropy with CAD, we may be able to improve the detection power of genetic variants associated with BMD. Using a recently developed conditional false discovery rate (cFDR) method, we jointly analyzed summary statistics from two large independent genome wide association studies (GWAS) of lumbar spine (LS) BMD and CAD. Strong pleiotropic enrichment and 7 pleiotropic SNPs were found for the two traits. We identified 41 SNPs for LS BMD (cFDR<0.05), of which 20 were replications of previous GWASs and 21 were potential novel SNPs that were not reported before. Four genes encompassed by 9 cFDR-significant SNPs were partially validated in the gene expression assay. Further functional enrichment analysis showed that genes corresponding to the cFDR-significant LS BMD SNPs were enriched in GO terms and KEGG pathways that played crucial roles in bone metabolism (adjP<0.05). In protein-protein interaction analysis, strong interactions were found between the proteins produced by the corresponding genes. Our study demonstrated the reliability and high-efficiency of the cFDR method on the detection of trait-associated genetic variants, the present findings shed novel insights into the genetic variability of BMD as well as the shared genetic basis underlying osteoporosis and CAD.

Increased identification of novel variants in type 2 diabetes, birth weight and their pleiotropic loci.

BACKGROUND: Clinical and epidemiological findings point to an association between type 2 diabetes (T2D) and low birth weight. However, the nature of the relationship is largely unknown. The aim of this study was to identify novel single nucleotide polymorphisms (SNPs) in T2D and birth weight, and their pleiotropic loci. METHODS: A pleiotropy-informed conditional false discovery rate (cFDR) method was applied to two independent genome-wide association studies (GWAS) summary statistics of T2D (n = 149 821) and birth weight (n = 26 836). RESULTS: A conditional Q-Q plot showed strong enrichment of genetic variants in T2D conditioned on different levels of association with birth weight. 133 T2D-associated SNPs, including 120 novel SNPs, were identified with a significance threshold of cFDR < 0.05; 13 significant birth weight-associated SNPs, including 12 novel SNPs (cFDR < 0.05) were identified. Conjunctional cFDR (ccFDR) analysis identified nine pleiotropic loci, including seven novel loci, shared by both T2D and birth weight (ccFDR < 0.05). Two novel SNPs located at the CDK5 regulatory subunit-associated protein 1-like 1 (CDKAL1; rs1012635; cFDR < 0.05) and adenylate cyclase 5 (ADCY5; rs4677887; cFDR < 0.05) genes are of note. These two genes increase the risk of T2D and low birth weight through the pathway of the "fetal insulin hypothesis." CONCLUSION: Several pleiotropic loci were identified between T2D and birth weight by leveraging GWAS results. The results make it possible to explain a greater proportion of trait heritability and improve our understanding of the shared pathophysiology between T2D and birth weight.

[Association of diabetes mellitus with biological behaviors of colorectal cancer].

OBJECTIVE: To evaluate the association of diabetes mellitus(DM) with colorectal cancer. METHODS: Case-control study was performed to compare 486 patients with colorectal cancer (study group) and 533 patients without colorectal cancer (control group) in the Affiliated Nanhai Hospital of Southern Medical University between 2006 and 2009. RESULTS: The incidence of DM was 12.1% in study group and 7.1% in the control group, and the difference was significant(P<0.01). On multivariate analysis, DM was independently associated with colorectal cancer (OR=1.886,95% CI:1.450~3.571). Colorectal cancer risk was increased in DM patients with a duration of 5-20 years(P<0.05), while colorectal cancer risk in those with a duration less than 5 years or more than 20 years did not change(P>0.05). No significant differences in tumor differentiation, invasion depth, lymph node involvement, distant metastasis and lymphovascular invasion were found between colorectal cancer patients with and without DM(all P>0.05). CONCLUSION: Diabetes mellitus increases the risk of colorectal cancer, however, biological behaviors of colorectal cancer is not associated with diabetes mellitus.