Decoding the gene-disease associations in type 2 diabetes: A curated dataset for text mining-based classification.

Type 2 Diabetes (T2D) exerts a substantial impact on mortality rates. According to 2023 statistics, more than half a billion individuals are experiencing the effects of T2D, making it one of the top 10 leading contributors to worldwide deaths. Multiple factors contribute to the onset of T2D, such as obesity, poor diet and lifestyle, the mutation in specific genes and many more. Among the various factors that contribute to the development of T2D, genetics is a pivotal aspect. Due to the significant influence of genes in the initiation and advancement of various phases of T2D, our focus lies on exploring the association between T2D and genes. In the present article, we have curated Standard disease gene association data which contains evidence or reference sentences which contain this disease gene association information, which is further classified into 4 classes: Yes, No, Ambiguous and X each pertaining to Positive, Negative, Ambiguous and Not related disease-gene associations respectively. For the purpose of this work, we downloaded T2D related abstracts from PubMed using EDirect and further pre-processed this abstract data to extract Reference Sentences Data. This data was later double-fold manually validated to compile this disease gene association data. The data produced in this article serves as reference data for the training text mining-based biological literature classifiers. Classifiers will further be used to predict classes of published literature, not just for T2D, but can also be expanded beyond to encompass a wide range of disease and their complications. The compilation of positively linked genes derived from these predictions can then be utilized for in-depth system-level analysis of T2D.

Paediatric diabetes subtypes in a consanguineous population: a single-centre cohort study from Kurdistan, Iraq.

AIMS/HYPOTHESIS: Monogenic diabetes is estimated to account for 1-6% of paediatric diabetes cases in primarily non-consanguineous populations, while the incidence and genetic spectrum in consanguineous regions are insufficiently defined. In this single-centre study we aimed to evaluate diabetes subtypes, obtain the consanguinity rate and study the genetic background of individuals with syndromic and neonatal diabetes in a population with a high rate of consanguinity. METHODS: Data collection was carried out cross-sectionally in November 2021 at the paediatric diabetic clinic, Dr Jamal Ahmad Rashed Hospital, in Sulaimani, Kurdistan, Iraq. At the time of data collection, 754 individuals with diabetes (381 boys) aged up to 16 years were registered. Relevant participant data was obtained from patient files. Consanguinity status was known in 735 (97.5%) participants. Furthermore, 12 families of children with neonatal diabetes and seven families of children with syndromic diabetes consented to genetic testing by next-generation sequencing. Prioritised variants were evaluated using the American College of Medical Genetics and Genomics guidelines and confirmed by Sanger sequencing. RESULTS: A total of 269 of 735 participants (36.5%) with known consanguinity status were offspring of consanguineous families. An overwhelming majority of participants (714/754, 94.7%) had clinically defined type 1 diabetes (35% of them were born to consanguineous parents), whereas only eight (1.1%) had type 2 diabetes (38% consanguineous). Fourteen (1.9%) had neonatal diabetes (50% consanguineous), seven (0.9%) had syndromic diabetes (100% consanguineous) and 11 (1.5%) had clinically defined MODY (18% consanguineous). We found that consanguinity was significantly associated with syndromic diabetes (p=0.0023) but not with any other diabetes subtype. The genetic cause was elucidated in ten of 12 participants with neonatal diabetes who consented to genetic testing (homozygous variants in GLIS3 [sibling pair], PTF1A and ZNF808 and heterozygous variants in ABCC8 and INS) and four of seven participants with syndromic diabetes (homozygous variants in INSR, SLC29A3 and WFS1 [sibling pair]). In addition, a participant referred as syndromic diabetes was diagnosed with mucolipidosis gamma and probably has type 2 diabetes. CONCLUSIONS/INTERPRETATION: This unique single-centre study confirms that, even in a highly consanguineous population, clinically defined type 1 diabetes is the prevailing paediatric diabetes subtype. Furthermore, a pathogenic cause of monogenic diabetes was identified in 83% of tested participants with neonatal diabetes and 57% of participants with syndromic diabetes, with most variants being homozygous. Causative genes in our consanguineous participants were markedly different from genes reported from non-consanguineous populations and also from those reported in other consanguineous populations. To correctly diagnose syndromic diabetes in consanguineous populations, it may be necessary to re-evaluate diagnostic criteria and include additional phenotypic features such as short stature and hepatosplenomegaly.

Effect of green cardamom on the expression of genes implicated in obesity and diabetes among obese women with polycystic ovary syndrome: a double blind randomized controlled trial.

BACKGROUND: Polycystic ovary syndrome (PCOS) is an endocrine disease in which related to obesity, metabolic disorders and is considered as one of the main causes of infertility in women. This trial was investigated the effects of green cardamom on the expression of genes implicated in obesity and diabetes among obese women with PCOS. METHODS: One hundred ninety-four PCOS women were randomly divided two groups: intervention (n = 99; 3 g/day green cardamom) and control groups (n = 95). All of them were given low calorie diet. Anthropometric, glycemic and androgen hormones were assessed before and after 16-week intervention. The reverse transcription-polymerase chain reaction (RT-PCR) method was used to measure fat mass and obesity-associated (FTO), peroxisome proliferative activating receptor- (PPAR-), carnitine palmitoyltransferase 1A (CPT1A), acetyl-CoA carboxylase beta (ACAB), leptin receptor (LEPR), ghrelin, and lamin A/C (LAMIN) genes expression in each group. RESULTS: Anthropometric indices were significantly decreased after intervention in both two studied groups. Glycemic indices and androgen hormones were significantly improved in the intervention group compared to the control group. The expression levels of FTO, CPT1A, LEPR, and LAMIN were significantly downregulated compared to control group (P < 0.001), as well as, PPAR-y was significantly upregulated in the intervention group after intervention with green cardamom compared to control group (P < 0.001). CONCLUSION: This current study showed that the administration of green cardamom is a beneficial approach for improving anthropometric, glycemic, and androgen hormones, as well as obesity and diabetes genes expression in PCOS women under the low-calorie diet. TRIAL REGISTRATION: This trial was registered with the Iranian Clinical Trials Registry (registration number: IRCT20200608047697N1). 1 August, 2020; https://www.irct.ir/trial/48748.

Porphyromonas gingivalis (W83) Infection Induces Alzheimer's Disease-Like Pathophysiology in Obese and Diabetic Mice.

BACKGROUND: Periodontal disease(s) and metabolic illnesses negatively impact the quality of life and, eventually mental health. OBJECTIVE: This study investigated the effect of Porphyromonas gingivalis (W83) oral infection on the development of Alzheimer's disease (AD) pathophysiology in a wild-type obese, diabetic (db/db) mouse model. METHODS: The db/db mice were either orally infected with P. gingivalis and Fusobacterium nucleatum or sham infected for 16 weeks. The presence of amyloid-ß (Aß) and neurofibrillary tangles (NFTs) were assessed using a silver impregnation technique and subsequently by immunohistochemistry for tau and neuroinflammation. The mRNA abundance of a panel of 184 genes was performed using quantitative real-time PCR, and the differentially expressed genes were analyzed by Ingenuity Pathway Analysis. RESULTS: While no Aß plaques and NFTs were evident by silver impregnation, immunohistochemistry (glial cell markers) of the P. gingivalis-infected mice tissue sections exhibited neuroinflammation in the form of reactive microglia and astrocytes. Anti-tau immunopositivity, in addition to cells, was prominent in thickened axons of hippocampal CA neurons. The mRNA abundance of crucial genes in the insulin signaling pathway (INSR, IGF1, IRS, IDE, PIK3R, SGK1, GYS, GSK3B, AKT1) were upregulated, potentially exacerbating insulin resistance in the brain by P. gingivalis oral infection. Increased mRNA abundance of several kinases, membrane receptors, transcription factors, and pro-inflammatory mediators indicated hyperactivation of intracellular cascades with potential for tau phosphorylation and Aß release in the same infection group. CONCLUSION: P. gingivalis W83 infection of db/db mice provides a disease co-morbidity model with the potential to reproduce AD pathophysiology with induced periodontal disease.

Type-2 diabetes-associated variants with cross-trait relevance: Post-GWAs strategies for biological function interpretation.

Genome-wide association studies (GWAs) for type 2 diabetes (T2D) have been successful in identifying many loci with robust association signals. Nevertheless, there is a clear need for post-GWAs strategies to understand mechanism of action and clinical relevance of these variants. The association of several comorbidities with T2D suggests a common etiology for these phenotypes and complicates the management of the disease. In this study, we focused on the genetics underlying these relationships, using systems genomics to identify genetic variation associated with T2D and 12 other traits. GWAs studies summary statistics for pairwise comparisons were obtained for glycemic traits, obesity, coronary artery disease, and lipids from large consortia GWAs meta-analyses. We used a network medicine approach to leverage experimental information about the identified genes and variants with cross traits effects for biological function interpretation. We identified a set of 38 genetic variants with cross traits effects that point to a main network of genes that should be relevant for T2D and its comorbidities. We prioritized the T2D associated genes based on the number of traits they showed association with and the experimental evidence showing their relation to the disease etiology. In this study, we demonstrated how systems genomics and network medicine approaches can shed light into GWAs discoveries, translating findings into a more therapeutically relevant context.