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.

Diabetes remission of bariatric surgery and nonsurgical treatments in type 2 diabetes patients who failure to meet the criteria for surgery: a systematic review and meta-analysis.

BACKGROUND: The efficacy of bariatric surgery in moderate and severe obesity patients to reach diabetes remission is clear, but for mild obesity patients, the choice of surgical and non-surgical treatment is still unclear. This study we aim to compare the effect of surgical and nonsurgical treatment on patients BMI < 35 kg/m2 to reach diabetes remission. METHOD: We searched relevant articles publish between Jan 1,2010 and Jan 1, 2023 in the following databases: Embase, PubMed/MEDLINE, Scopus, and Cochrane Library. We got the OR, MD and P-value using random effect model to compare the efficiency between bariatric surgery and nonsurgical treatment on diabetes remission, the reduction of BMI, Hb1Ac and FPG. RESULTS: In 7 included studies including 544 participants, bariatric surgery is more effective than non-surgical treatment to reach diabetes remission [OR 25.06, 95%CL 9.58-65.54]. Bariatric surgery more likely resulted in significant reductions in HbA1c [MD -1.44, 95%CL (-1.84)-(-1.04)] and FPG [MD -2.61, 95%CL (-3.20)-(-2.20)]. Bariatric surgery may resulted in reductions in BMI [MD -3.14, 95%CL (-4.41)-(-1.88)], which more significant in Asian. CONCLUSION: In type 2 diabetes patients who BMI < 35 kg/m2, bariatric surgery is more likely to achieve diabetes remission and better blood glucose control than nonsurgical treatment.

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.

Effects of Low-Dose Spironolactone Combined with Metformin or Either Drug Alone on Insulin Resistance in Patients with Polycystic Ovary Syndrome: A Pilot Study.

Metformin and spironolactone alone can be used for the management of polycystic ovarian syndrome (PCOS), and their combination could result in even better outcomes. To compare the effects and safety of low-dose spironolactone combined with metformin or either drug alone on insulin resistance (IR) and functional improvement in patients with PCOS, this was a single-center, randomized, open-label, pilot study of patients with PCOS at the Third Affiliated Hospital of Guangzhou Medical University between 01/2014 and 01/2016. The participants were randomized 1 : 1 : 1 to metformin, spironolactone, or metformin + spironolactone. The primary endpoint was the change in the homeostatic model assessment (HOMA)-IR after 12 weeks of treatment. A total of 189 participants were randomized (63 per group); 31 dropped out, and 54, 51, and 53 completed the 12-week treatment in the metformin, spironolactone, and combined groups, respectively. There were no differences in any parameters between the metformin and spironolactone groups (all P > 0.05). In the combined group, after 12 weeks of treatment, HOMA-IR (1.71 ± 0.91) was lower than in the metformin (1.92 ± 1.07, P < 0.05) and spironolactone (2.38 ± 1.14, P < 0.05) groups. In addition, total testosterone (TT), free androgen index (FAI), and area under the curve-insulin (AUCins) were lower in the combined group compared with the metformin group (all P < 0.05), while TT, FAI, HOMA-ß, fasting plasma glucose, and AUCins were lower in the spironolactone group (all P < 0.05). Both metformin and spironolactone decreased HOMA-IR in patients with PCOS but without differences between the two monotherapies. The combined therapy decreased HOMA-IR to a greater extent than monotherapy.

Research on On-Line Detection Method of Transformer Winding Deformation Based on VFTO.

At present, the detection of transformer winding deformation faults is carried out in an offline state, which requires the transformer to cooperate with the implementation of planned power outages, or it takes place after the sudden failure of the transformer when it is out of operation. It is difficult to obtain the status information of the windings online in time. Since the transformer will suffer very fast transient overvoltage (VFTO) impact during operation, combined with the principle of the frequency response method, an online detection method of transformer winding deformation based on VFTO is proposed. In order to study the frequency response characteristics of transformer winding under the impact of VFTO, the generation process of VFTO is simulated by simulation software, and the equivalent circuit model of transformer winding before and after deformation is established. The VFTO signal is injected into the transformer circuit model as an excitation source, and the changes of resonant frequencies of frequency response curve under different deformation types and different deformation degrees of winding are analyzed. The simulation results show that the frequency response curves of different winding deformation types are different. Different deformation degrees are simulated by increasing the radial capacitance by 4%, 13%, and 23%, series inductance by 2%, 4%, and 6%, and longitudinal capacitance by 3%, 6%, and 9%, and the change of resonance frequencies can comprehensively reflect the deformation information of winding. At the same time, the tests of different deformation types and deformation degrees of the simulated winding are carried out. The results show that with the deepening of the change degree of the simulated fault inductance value, the frequency response curve shifts to the low-frequency direction, confirming the feasibility of the online detection method of transformer winding deformation based on VFTO.

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.

Plasma glucose to glycated hemoglobin ratio: Method of differentiating fulminant type 1 diabetes from diabetic ketoacidosis.

OBJECTIVES: In fulminant type 1 diabetes mellitus (fT1DM), plasma glucose (PG) levels are strongly increased, unlike glycated hemoglobin (HbA1C) levels, resulting in a sharply increased PG/HbA1C ratio. We investigated the PG/HbA1C ratio in fT1DM and tested the accuracy of cutoff points to easily and efficiently differentiate fT1DM from diabetic ketoacidosis (DKA). METHODS: We report 41 cases of fT1DM in which PG/HbA1C ratio was studied as a novel clinical parameter to predict fT1DM. Clinical and biochemical characteristics were analyzed in 41 fT1DM and 51 DKA patients in China. Receiver-operating characteristic curve analysis was used to identify PG/HbA1C ratio cutoff points to differentiate fT1DM from DKA. RESULTS: PG/HbA1C ratio was significantly higher in fT1DM patients (7.24±2.49mmol/L/%; i.e., 0.88±0.36L/mol) than in DKA patients (2.60±0.69mmol/L/%; i.e., 0.06±0.01L/mol) (P<0.001). PG/HbA1C ratio exceeded 4.2mmol/L/% (i.e., 0.6 l/mol) in 39 of the 41 fT1DM patients (95.1%), versus only 1 of the 51 DKA patients (1.9%). CONCLUSIONS: PG/HbA1C ratio is a simple tool that may be useful to identify DKA patients at high risk of fT1DM. PG/HbA1C ratio with a threshold of≥4.2mmol/L/% (i.e., 0.6L/mol) can be adopted as a new clinical parameter in predicting fT1DM.

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.

Integrative functional analysis of super enhancer SNPs for coronary artery disease.

Clinical research in coronary artery disease (CAD) primarily focused on genetic variants located in protein-coding regions. Recently, mutations fall within non-coding regions have been suggested to be essential to the pathogenesis of human complex disease. Super enhancer is a densely spaced cluster of transcriptional enhancers located in non-coding regions, which is critical for regulating cell-type specific gene expression. However, the underlying mechanism of the super enhancer single-nucleotide polymorphisms (SNPs) affecting the risk of CAD remains unclear. By integrating genome-wide association study (GWAS) meta-analysis of CAD and cell/tissue-specific histone modification data set, we identified 366 potential CAD-associated super enhancer SNPs in 67 loci, including 94 SNPs that are involved in regulating chromatin interactive and/or affecting the transcription factors binding affinity. Interestingly, we found 7 novel functional loci (CBFA2T3, ZMIZ1, DIP2B, SCNN1D/ACAP3, TMEM105, CAMK2G, and MAPK1) that CAD-associated super enhancer SNPs were clustered into the same or neighboring super enhancers. Pathway analysis showed a significant enrichment in several well-known signaling and regulatory processes, e.g., cAMP signaling pathway and ErbB signaling pathway, which play a key role in CAD metabolism. Our results highlight the potential functional importance of CAD-associated super enhancer SNPs and provide the targets for further insights on the pathogenesis of CAD.

Integrative analysis of super enhancer SNPs for type 2 diabetes.

Clinical studies in type 2 diabetes (T2D) primarily focused on the single nucleotide polymorphisms (SNPs) located in protein-coding regions. Recently, the SNPs located in noncoding regions have also been recognized to play an important role in disease susceptibility. The super enhancer is a cluster of transcriptional enhancers located in noncoding regions. It plays a critical role in cell-type specific gene expression. However, the exact mechanism of the super enhancer SNPs for T2D remains unclear. In this study, we integrated genome-wide association studies (GWASs) and T2D cell/tissue-specific histone modification ChIP-seq data to identify T2D-associated SNPs in super enhancer, followed by comprehensive bioinformatics analyses to further explore the functional importance of these SNPs. We identified several interesting T2D super enhancer SNPs. Interesting, most of them were clustered within the same or neighboring super enhancers. A number of SNPs are involved in chromatin interactive regulation and/or potentially influence the binding affinity of transcription factors. Gene Ontology (GO) analysis showed a significant enrichment in several well-known signaling pathways and regulatory process, e.g. WNT signaling pathway, which plays a key role in T2D metabolism. Our results highlighted the potential functional importance of T2D super enhancer SNPs, which may yield novel insights into the pathogenesis of T2D.

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.

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.

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.