Assessment of smell disturbances 6 months after COVID-19 in Polish population.

Considering the frequency and severity of olfactory disorders associated with SARS-CoV-2 infection, attention to the olfactory loss has expanded. The aim of our study was to assess of smell disturbances 6 months after COVID-19. The study population consisted of 2 groups: 196 Post-COVID-19 patients who were hospitalized because of COVID-19, control sample-130 patients without reported smell disorders from general population-Bialystok PLUS study. People from both groups were asked to participate in the Sniffin Sticks Test (half year after the disease). Sniffin Sticks Test consisted of 12 standardized smell samples. The participant's test score was counted based on correct scent recognition. Middle/older age was related with lower likelihood of olfaction recovery. The biggest differences in recognition of particular fragrances were observed for: orange and lemon, lemon and coffee (p.adj < 0.001). Patients had the greatest problem in assessing smell of lemon. The comparison of scores between Delta, Omicron, Wild Type, Wild Type Alpha waves showed statistically significant difference between Delta and Wild Type waves (p = 0.006). Duration of the disease (r = 0.218), age (r = -0.253), IL-6 (r = -0.281) showed significant negative correlations with the score. Statistically significant variables in the case of smell disorders were Omicron wave (CI = 0.045-0.902; P = 0.046) and Wild Type wave (CI = 0.135-0.716; P = 0.007) compared to Delta wave reference. Moreover, patients with PLT count below 150 000/µl had greater olfactory disorders than those with PLT count over 150 000/µl. There are: smell differences between post-COVID-19 patients and healthy population; statistically significant difference between Delta and Wild Type waves in Post-COVID-19 group in score of the Sniffin Sticks Test. Smell disturbances depend on the age, cognitive impairments, clinical characteristics of the COVID-19 disease and sex of the patient.

Dietary factors and their influence on immunotherapy strategies in oncology: a comprehensive review.

Immunotherapy is emerging as a promising avenue in oncology, gaining increasing importance and offering substantial advantages when compared to chemotherapy or radiotherapy. However, in the context of immunotherapy, there is the potential for the immune system to either support or hinder the administered treatment. This review encompasses recent and pivotal studies that assess the influence of dietary elements, including vitamins, fatty acids, nutrients, small dietary molecules, dietary patterns, and caloric restriction, on the ability to modulate immune responses. Furthermore, the article underscores how these dietary factors have the potential to modify and enhance the effectiveness of anticancer immunotherapy. It emphasizes the necessity for additional research to comprehend the underlying mechanisms for optimizing the efficacy of anticancer therapy and defining dietary strategies that may reduce cancer-related morbidity and mortality. Persistent investigation in this field holds significant promise for improving cancer treatment outcomes and maximizing the benefits of immunotherapy.

Multi-ancestry polygenic mechanisms of type 2 diabetes.

Type 2 diabetes (T2D) is a multifactorial disease with substantial genetic risk, for which the underlying biological mechanisms are not fully understood. In this study, we identified multi-ancestry T2D genetic clusters by analyzing genetic data from diverse populations in 37 published T2D genome-wide association studies representing more than 1.4 million individuals. We implemented soft clustering with 650 T2D-associated genetic variants and 110 T2D-related traits, capturing known and novel T2D clusters with distinct cardiometabolic trait associations across two independent biobanks representing diverse genetic ancestral populations (African, n = 21,906; Admixed American, n = 14,410; East Asian, n =2,422; European, n = 90,093; and South Asian, n = 1,262). The 12 genetic clusters were enriched for specific single-cell regulatory regions. Several of the polygenic scores derived from the clusters differed in distribution among ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a body mass index (BMI) of 30 kg m-2 in the European subpopulation and 24.2 (22.9-25.5) kg m-2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg m-2 in the East Asian group. Thus, these multi-ancestry T2D genetic clusters encompass a broader range of biological mechanisms and provide preliminary insights to explain ancestry-associated differences in T2D risk profiles.

Long-term effects of COVID-19 on the endocrine system - a pilot case-control study.

Background: Coronavirus disease 2019 (COVID-19) has permanently changed the world. Despite having been a pandemic for nearly 3 years, the mid- and long-term complications of this disease, including endocrine disorders, remain unclear. Our study aimed to evaluate the lasting effects of COVID-19 on the endocrine system 6 months after initial infection. Methods: We compared patients who underwent COVID-19 to age- and sex-matched subjects from a population-based study conducted before the pandemic. We evaluated differences in multiple parameters related to metabolism and the endocrine system including fasting glucose, insulin, lipids, body composition, thyroid stimulating hormone (TSH), free thyroxine (fT4), free triiodothyronine (fT3), anti-thyroglobulin (aTG) and anti-thyroid peroxidase (aTPO) antibodies, prolactin, cortisol, testosterone, and estradiol. Results: We found significantly lower levels of fT3 and fT4, accompanied by higher levels of TSH and aTPO antibodies, in COVID-19 survivors. Moreover, we found that patients who underwent SARS-CoV2 infection had higher levels of prolactin and lower levels of testosterone than controls. Interestingly, differences in testosterone levels were observed only in male subjects. We did not detect significant differences in body composition or metabolic and glycemic parameters between cases and controls, except for significantly higher values of the HOMA2-B index in COVID-19 survivors. Conclusion: Our study indicates that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection might have long-term consequences on the endocrine system, including the suppressed function of the thyroid gland, prolactin, and male sex hormone secretion. Moreover, we showed that in a 6-month follow-up, COVID-19 had no consequences on glycemic parameters, lipid profiles, liver function, body composition, cortisol levels, and estradiol levels.

Precision medicine of obesity as an integral part of type 2 diabetes management - past, present, and future.

Obesity is a complex and heterogeneous condition that leads to various metabolic complications, including type 2 diabetes. Unfortunately, for some, treatment options to date for obesity are insufficient, with many people not reaching sustained weight loss or having improvements in metabolic health. In this Review, we discuss advances in the genetics of obesity from the past decade-with emphasis on developments from the past 5 years-with a focus on metabolic consequences, and their potential implications for precision management of the disease. We also provide an overview of the potential role of genetics in guiding weight loss strategies. Finally, we propose a vision for the future of precision obesity management that includes developing an obesity-centred multidisease management algorithm that targets both obesity and its comorbidities. However, further collaborative efforts and research are necessary to fully realise its potential and improve metabolic health outcomes.

Multi-ancestry Polygenic Mechanisms of Type 2 Diabetes Elucidate Disease Processes and Clinical Heterogeneity.

We identified genetic subtypes of type 2 diabetes (T2D) by analyzing genetic data from diverse groups, including non-European populations. We implemented soft clustering with 650 T2D-associated genetic variants, capturing known and novel T2D subtypes with distinct cardiometabolic trait associations. The twelve genetic clusters were distinctively enriched for single-cell regulatory regions. Polygenic scores derived from the clusters differed in distribution between ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a BMI of 30 kg/m2 in the European subpopulation and 24.2 (22.9-25.5) kg/m2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg/m2 in the East Asian group, explaining about 75% of the difference in BMI thresholds. Thus, these multi-ancestry T2D genetic subtypes encompass a broader range of biological mechanisms and help explain ancestry-associated differences in T2D risk profiles.

The FCGR2A Is Associated with the Presence of Atherosclerotic Plaques in the Carotid Arteries-A Case-Control Study.

BACKGROUND: Atherosclerotic plaques in carotid arteries (APCA) are a prevalent condition with severe potential complications. Studies continuously search for innovative biomarkers for APCA, including those participating in cellular metabolic processes, cell adhesion, immune response, and complement activation. This study aimed to assess the relationship between APCA presence and a broad range of cardiometabolic biomarkers in the general population. METHODS: The study group consisted of consecutive participants of the population study Bialystok PLUS. The proximity extension assay (PEA) technique from the Olink Laboratory (Uppsala, Sweden) was used to measure the levels of 92 cardiometabolic biomarkers. RESULTS: The study comprised 693 participants (mean age 48.78 ± 15.27 years, 43.4% males, N = 301). APCA was identified in 46.2% of the participants (N = 320). Of the 92 biomarkers that were investigated, 54 were found to be significantly linked to the diagnosis of APCA. After adjusting for the traditional risk factors for atherosclerosis in multivariate analysis, the only biomarker that remained significantly associated with APCA was FCGR2A. CONCLUSION: In the general population, the prevalence of APCA is very high. A range of biomarkers are linked with APCA. Nonetheless, the majority of these associations are explained by traditional risk factors for atherosclerosis. The only biomarker that was independently associated with APCA was the FCGR2A.

Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes.

We meta-analyzed array data imputed with the TOPMed reference panel and whole-genome sequence (WGS) datasets and performed the largest, rare variant (minor allele frequency as low as 5×10-5) GWAS meta-analysis of type 2 diabetes (T2D) comprising 51,256 cases and 370,487 controls. We identified 52 novel variants at genome-wide significance (p<5 × 10-8), including 8 novel variants that were either rare or ancestry-specific. Among them, we identified a rare missense variant in HNF4A p.Arg114Trp (OR=8.2, 95% confidence interval [CI]=4.6-14.0, p = 1.08×10-13), previously reported as a variant implicated in Maturity Onset Diabetes of the Young (MODY) with incomplete penetrance. We demonstrated that the diabetes risk in carriers of this variant was modulated by a T2D common variant polygenic risk score (cvPRS) (carriers in the top PRS tertile [OR=18.3, 95%CI=7.2-46.9, p=1.2×10-9] vs carriers in the bottom PRS tertile [OR=2.6, 95% CI=0.97-7.09, p = 0.06]. Association results identified eight variants of intermediate penetrance (OR>5) in monogenic diabetes (MD), which in aggregate as a rare variant PRS were associated with T2D in an independent WGS dataset (OR=4.7, 95% CI=1.86-11.77], p = 0.001). Our data also provided support evidence for 21% of the variants reported in ClinVar in these MD genes as benign based on lack of association with T2D. Our work provides a framework for using rare variant imputation and WGS analyses in large-scale population-based association studies to identify large-effect rare variants and provide evidence for informing variant pathogenicity.

Multi-ancestry Polygenic Mechanisms of Type 2 Diabetes Elucidate Disease Processes and Clinical Heterogeneity.

We identified genetic subtypes of type 2 diabetes (T2D) by analyzing genetic data from diverse groups, including non-European populations. We implemented soft clustering with 650 T2D-associated genetic variants, capturing known and novel T2D subtypes with distinct cardiometabolic trait associations. The twelve genetic clusters were distinctively enriched for single-cell regulatory regions. Polygenic scores derived from the clusters differed in distribution between ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a BMI of 30 kg/m2 in the European subpopulation and 24.2 (22.9-25.5) kg/m2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg/m2 in the East Asian group, explaining about 75% of the difference in BMI thresholds. Thus, these multi-ancestry T2D genetic subtypes encompass a broader range of biological mechanisms and help explain ancestry-associated differences in T2D risk profiles.

Algorithms for the identification of prevalent diabetes in the All of Us Research Program validated using polygenic scores - a new resource for diabetes precision medicine.

OBJECTIVE: The study aimed to develop and validate algorithms for identifying people with type 1 and type 2 diabetes in the All of Us Research Program (AoU) cohort, using electronic health record (EHR) and survey data. RESEARCH DESIGN AND METHODS: Two sets of algorithms were developed, one using only EHR data (EHR), and the other using a combination of EHR and survey data (EHR+). Their performance was evaluated by testing their association with polygenic scores for both type 1 and type 2 diabetes. RESULTS: For type 1 diabetes, the EHR-only algorithm showed a stronger association with T1D polygenic score (p=3×10-5) than the EHR+. For type 2 diabetes, the EHR+ algorithm outperformed both the EHR-only and the existing AoU definition, identifying additional cases (25.79% and 22.57% more, respectively) and showing stronger association with T2D polygenic score (DeLong p=0.03 and 1×10-4, respectively). CONCLUSIONS: We provide new validated definitions of type 1 and type 2 diabetes in AoU, and make them available for researchers. These algorithms, by ensuring consistent diabetes definitions, pave the way for high-quality diabetes research and future clinical discoveries.

Assessment of the Immune Response in Patients with Insulin Resistance, Obesity, and Diabetes to COVID-19 Vaccination.

The SARS-CoV-19 pandemic overwhelmed multiple healthcare systems across the world. Patients with underlying medical conditions such as obesity or diabetes were particularly vulnerable, had more severe symptoms, and were more frequently hospitalized. To date, there have been many studies on the severity of SARS-CoV-2 in patients with metabolic disorders, but data on the efficiency of vaccines against COVID-19 are still limited. This paper aims to provide a comprehensive overview of the effectiveness of COVID-19 vaccines in individuals with diabetes, insulin resistance, and obesity. A comparison is made between the immune response after vaccination in patients with and without metabolic comorbidities. Additionally, an attempt is made to highlight the mechanisms of immune stimulation affected by SARS-CoV-2 vaccines and how metabolic comorbidities modulate these mechanisms. The focus is on the most common COVID-19 vaccines, which include mRNA vaccines such as Pfizer-BioNTech and Moderna, as well as viral vector vaccines such as AstraZeneca and Johnson & Johnson. Furthermore, an effort is made to clarify how the functional differences between these vaccines may impact the response in individuals with metabolic disorders, drawing from available experimental data. This review summarizes the current knowledge regarding the post-vaccination response to COVID-19 in the context of metabolic comorbidities such as diabetes, insulin resistance, and obesity.

The Effect of Laparoscopic Sleeve Gastrectomy on the Course of Non-Alcoholic Fatty Liver Disease in Morbidly Obese Patients during One Year of Follow Up.

BACKGROUND: Morbid obesity co-exists with non-alcoholic fatty liver disease in up to 90% of cases. Laparoscopic sleeve gastrectomy leads to a reduction in body mass and thus may improve the course of non-alcoholic fatty liver disease. The aim of this study was to evaluate the effect of laparoscopic sleeve gastrectomy on the resolution of non-alcoholic fatty liver disease. METHODS: The study included 55 patients with non-alcoholic fatty liver disease who underwent laparoscopic sleeve gastrectomy at a tertiary institution. The analysis consisted of preoperative liver biopsy, abdominal ultrasound, weight loss parameters, Non-Alcoholic Fatty Liver Fibrosis Score and selected laboratory parameters. RESULTS: Before the surgery, 6 patients were diagnosed with grade 1 liver steatosis, 33 patients with grade 2 and 16 patients with grade 3. One year after the surgery, only 21 patients had features of liver steatosis at ultrasound. All weight loss parameters showed statistically significant changes during the observation; the median percentage of total weight loss was 31.0% (IQR: 27.5; 34.5) with p = 0.0003, the median percentage of excess weight loss was 61.8% (IQR: 52.4; 72.3) with p = 0.0013 and the median percentage of excess body mass index loss was 71.0% (IQR: 61.3; 86.9) with p = 0.0036 12 months after laparoscopic sleeve gastrectomy. The median Non-Alcoholic Fatty Liver Fibrosis Score at baseline was 0.2 (IQR: -0.8; 1.0) and decreased to -1.6 (IQR: -2.4; -0.4) (p < 0.0001). Moderate negative correlations between Non-Alcoholic Fatty Liver Fibrosis Score and percentage of total weight loss (r = -0.434, p < 0.0001), percentage of excess weight loss (r = -0.456, p < 0.0001) and percentage of excess body mass index loss (r = -0.512, p < 0.0001) were found. CONCLUSIONS: The study supports the thesis that laparoscopic sleeve gastrectomy is an effective method for treatment of non-alcoholic fatty liver disease in patients with morbid obesity.

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes.

AIMS/HYPOTHESIS: The Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population. METHODS: We evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort. RESULTS: Compared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p=3.4 × 10-9). A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improved the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance. CONCLUSIONS/INTERPRETATION: Our results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores. DATA AVAILABILITY: Full summary statistics are available through the Common Metabolic Diseases Knowledge Portal ( https://t2d.hugeamp.org/downloads.html ) and through the GWAS catalog ( https://www.ebi.ac.uk/gwas/ , accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog ( https://www.pgscatalog.org , publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445).

Immune Response to Vaccination against COVID-19 at Different Second-Dose Intervals and Their Associations with Metabolic Parameters.

Obesity and diabetes are associated with severe outcomes of coronavirus disease (COVID-19). Vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been proven protective against infection and severe COVID-19. However, the immune response of metabolically burdened individuals to the vaccines remains unclear. Thus, we aimed to assess whether the metabolic status of individuals affects their humoral immune responses to the vaccination. Moreover, we evaluated whether the interval between the first two doses influenced antibody concentration. Sixty-seven individuals (21 males, 46 females) were vaccinated with the BNT162b2 mRNA COVID-19 vaccine. Fifty-four individuals were vaccinated with the second dose after 3 weeks and 13 after 5 weeks. We measured the antibody titers in all participants during the 19-week follow-up period. Patients diagnosed with COVID-19 were excluded. In the 5-week interval group, a significantly higher level of maximal antibody titers was observed. However, there were no differences in antibody concentrations after 19 weeks and no significant correlation between cardiometabolic factors and humoral response. The elongation of second-dose timing to 5 weeks leads to a higher acute antibody response but does not change long-term levels of antibody titers. Moreover, dysregulation of metabolic parameters does not lead to a diminished immune response to vaccination.

Testing the Utility of Polygenic Risk Scores for Type 2 Diabetes and Obesity in Predicting Metabolic Changes in a Prediabetic Population: An Observational Study.

Prediabetes is an intermediate state of hyperglycemia during which glycemic parameters are above normal levels but below the T2D threshold. T2D and its precursor prediabetes affect 6.28% and 7.3% of the world's population, respectively. The main objective of this paper was to create and compare two polygenic risk scores (PRSs) versus changes over time (Δ) in metabolic parameters related to prediabetes and metabolic complications. The genetics of 446 prediabetic patients from the Polish Registry of Diabetes cohort were investigated. Seventeen metabolic parameters were measured and compared at baseline and after five years using statistical analysis. Subsequently, genetic polymorphisms present in patients were determined to build a T2D PRS (68 SNPs) and an obesity PRS (21 SNPs). Finally, the association among the two PRSs and the Δ of the metabolic traits was assessed. After a multiple linear regression with adjustment for age, sex, and BMI at a nominal significance of (p < 0.05) and adjustment for multiple testing, the T2D PRS was found to be positively associated with Δ fat mass (FM) (p = 0.025). The obesity PRS was positively associated with Δ FM (p = 0.023) and Δ 2 h glucose (p = 0.034). The comparison of genotype frequencies showed that AA genotype carriers of rs10838738 were significantly higher in Δ 2 h glucose and in Δ 2 h insulin. Our findings suggest that prediabetic individuals with a higher risk of developing T2D experience increased Δ FM, and those with a higher risk of obesity experience increased Δ FM and Δ two-hour postprandial glucose. The associations found in this research could be a powerful tool for identifying prediabetic individuals with an increased risk of developing T2D and obesity.

COVID-19 pandemic influence on self-reported health status and well-being in a society.

To assess the frequency of persisting symptoms after SARS-CoV-2 infection and assessment of the effects of COVID-19 pandemic on selected parameters of self-reported health status and well-being half a year after the disease. The study population consisted of 3 groups: post-COVID-19 group I-172 patients; group II-172 patients with chronic disease, who have not suffered from COVID-19; group III-81 patients from a population study cohort-Bialystok PLUS. A standardized interview questionnaire was used to collect data in the three groups using the CATI (computer assisted telephone interviewing) technique. Interviews were conducted between October 2020 and January 2021, thus during the second wave of the pandemic in Poland. The subjective state of health in comparison with the state of health before the COVID-19 pandemic deteriorated in COVID-19 convalescents. Patients, who suffered from symptomatic COVID-19 were more prone to nervousness, anxiousness, tension than patients with oligosymptomatic course of the disease. Moreover, anxiety, fear and irritability were more frequent in Group I and II in comparison to Group III, whereas Group I and II did not differ significantly. The decrease in physical activity observed in COVID-19 patients mirrored the changes in general population. The most frequent persistent symptoms after COVID-19 are: general malaise, cough, smell and taste disorder, dyspnea. COVID-19 convalescents who experienced symptomatic disease are more prone to development of nervousness, anxiousness, tension and anxiety than patients with oligosymptomatic course of the disease. Females and younger patients who suffered from COVID-19 are more prone to development of mental distress than healthy population. No significant differences between COVID-19 convalescents and healthy population was observed as far as the attitude towards physical activity is concerned.

Risk Factors for Early and Late Complications after Laparoscopic Sleeve Gastrectomy in One-Year Observation.

BACKGROUND: Although laparoscopic sleeve gastrectomy (LSG) is considered a safe bariatric procedure in the treatment of obesity, it still involves a risk of developing postoperative complications. Knowledge of risk factors for possible complications would allow appropriate preoperative planning, optimization of postoperative care, as well as early diagnosis and treatment. The aim of this study was to evaluate risk factors for complications after laparoscopic sleeve gastrectomy. METHODS: A retrospective study of 610 patients who underwent LSG at a tertiary institution were included in the study through retrospective analysis of the medical data. Complications were categorized as early (<30 days) and late (≥30 days) and evaluated according to the Clavien-Dindo Classification. RESULTS: Early complications were observed in 35 patients (5.74%) and late complications occurred in 10 patients (1.64%). Independent risk factors of early complications after laparoscopic sleeve gastrectomy included hypercholesterolemia (OR 3.73; p-value = 0.023) and smoking (OR = 274.66, p-value < 0.001). Other factors that may influence the postoperative course are length of hospital stay and operation time. Smoking, peptic ulcer diseases and co-existence of hiatal hernia were found to be an independent predictors of late complications. CONCLUSIONS: Smoking is associated with the higher risk of both, early and late complications, while hypercholesterolemia with only <30 days complications after laparoscopic sleeve gastrectomy.

Exploring microRNAs as predictive biomarkers for type 2 diabetes mellitus remission after sleeve gastrectomy: A pilot study.

OBJECTIVE: This study aimed to evaluate microRNAs (miRNAs) as predictive biomarkers for type 2 diabetes (T2D) remission 12 months after sleeve gastrectomy (SG). METHODS: A total of 179 serum miRNAs were profiled, and 26 clinical variables were collected from 46 patients. Two patients were later excluded because of hemolysis, and six patients with unclear remission status were set aside to evaluate the prediction models. The remaining 38 patients were included for model building. Variable selection was done using different approaches, including Least Absolute Shrinkage and Selection Operator (LASSO). Prediction models were then developed using LASSO and assessed in the validation set. RESULTS: A total of 26 out of 38 patients achieved T2D remission 12 months after SG. The prediction model with only clinical variables misclassified two patients, which were correctly classified using miRNAs. Two miRNA-only models achieved an accuracy of one but performed poorly for the validation set. The best miRNA model was a mixed model (accuracy: 0.974) containing four miRNAs (hsa-miR-32-5p, hsa-miR-382-5p, hsa-miR-1-3p, and hsa-miR-21-5p) and four clinical variables (T2D medication, sex, age, and fasting blood glucose). These miRNAs are involved in pathways related to obesity and insulin resistance. CONCLUSIONS: This study suggests that four serum miRNAs might be predictive biomarkers for T2D remission 12 months after SG, but further validation studies are needed.