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

Type 2 diabetes (T2D) genome-wide association studies (GWASs) often overlook rare variants as a result of previous imputation panels' limitations and scarce whole-genome sequencing (WGS) data. We used TOPMed imputation and WGS to conduct the largest T2D GWAS meta-analysis involving 51,256 cases of T2D and 370,487 controls, targeting variants with a minor allele frequency as low as 5 × 10-5. We identified 12 new variants, including a rare African/African American-enriched enhancer variant near the LEP gene (rs147287548), associated with fourfold increased T2D risk. We also identified a rare missense variant in HNF4A (p.Arg114Trp), associated with eightfold increased T2D risk, previously reported in maturity-onset diabetes of the young with reduced penetrance, but observed here in a T2D GWAS. We further leveraged these data to analyze 1,634 ClinVar variants in 22 genes related to monogenic diabetes, identifying two additional rare variants in HNF1A and GCK associated with fivefold and eightfold increased T2D risk, respectively, the effects of which were modified by the individual's polygenic risk score. For 21% of the variants with conflicting interpretations or uncertain significance in ClinVar, we provided support of being benign based on their lack of association with T2D. Our work provides a framework for using rare variant GWASs to identify large-effect variants and assess variant pathogenicity in monogenic diabetes genes.

Association between plausible genetic factors and weight loss from GLP1-RA and bariatric surgery: a multi-ancestry study in 10 960 individuals from 9 biobanks.

Obesity is a significant public health concern. GLP-1 receptor agonists (GLP1-RA), predominantly in use as a type 2 diabetes treatment, are a promising pharmacological approach for weight loss, while bariatric surgery (BS) remains a durable, but invasive, intervention. Despite observed heterogeneity in weight loss effects, the genetic effects on weight loss from GLP1-RA and BS have not been extensively explored in large sample sizes, and most studies have focused on differences in race and ethnicity, rather than genetic ancestry. We studied whether genetic factors, previously shown to affect body weight, impact weight loss due to GLP1-RA therapy or BS in 10,960 individuals from 9 multi-ancestry biobank studies in 6 countries. The average weight change between 6 and 12 months from therapy initiation was -3.93% for GLP1-RA users, with marginal differences across genetic ancestries. For BS patients the weight change between 6 and 48 months from the operation was -21.17%. There were no significant associations between weight loss due to GLP1-RA and polygenic scores for BMI or type 2 diabetes or specific missense variants in the GLP1R, PCSK1 and APOE genes, after multiple-testing correction. However, a higher polygenic score for BMI was significantly linked to lower weight loss after BS (+0.7% for 1 standard deviation change in the polygenic score, P = 1.24×10-4). In contrast, higher weight at baseline was associated with greater weight loss. Our findings suggest that existing polygenic scores related to weight and type 2 diabetes and missense variants in the drug target gene do not have a large impact on GLP1-RA effectiveness. Our results also confirm the effectiveness of these treatments across all major continental ancestry groups considered.

Exploring protein relative relations in skeletal muscle proteomic analysis for insights into insulin resistance and type 2 diabetes.

The escalating prevalence of insulin resistance (IR) and type 2 diabetes mellitus (T2D) underscores the urgent need for improved early detection techniques and effective treatment strategies. In this context, our study presents a proteomic analysis of post-exercise skeletal muscle biopsies from individuals across a spectrum of glucose metabolism states: normal, prediabetes, and T2D. This enabled the identification of significant protein relationships indicative of each specific glycemic condition. Our investigation primarily leveraged the machine learning approach, employing the white-box algorithm relative evolutionary hierarchical analysis (REHA), to explore the impact of regulated, mixed mode exercise on skeletal muscle proteome in subjects with diverse glycemic status. This method aimed to advance the diagnosis of IR and T2D and elucidate the molecular pathways involved in its development and the response to exercise. Additionally, we used proteomics-specific statistical analysis to provide a comparative perspective, highlighting the nuanced differences identified by REHA. Validation of the REHA model with a comparable external dataset further demonstrated its efficacy in distinguishing between diverse proteomic profiles. Key metrics such as accuracy and the area under the ROC curve confirmed REHA's capability to uncover novel molecular pathways and significant protein interactions, offering fresh insights into the effects of exercise on IR and T2D pathophysiology of skeletal muscle. The visualizations not only underscored significant proteins and their interactions but also showcased decision trees that effectively differentiate between various glycemic states, thereby enhancing our understanding of the biomolecular landscape of T2D.

Apigenin's Modulation of Doxorubicin Efficacy in Breast Cancer.

Apigenin, a naturally derived flavonoid, is increasingly being acknowledged for its potential therapeutic applications, especially in oncology. This research explores apigenin's capacity to modulate cancer cell viability, emphasizing its roles beyond its minimal antioxidant activity attributed to its basic molecular structure devoid of hydroxyl groups. We investigated apigenin's effects on two breast cancer cell lines, estrogen-dependent MCF-7 and non-estrogen-dependent MDA-MB-231 cells. Our findings reveal that apigenin exerts a dose-dependent cytotoxic and anti-migratory impact on these cells. Interestingly, both apigenin and doxorubicin-a standard chemotherapeutic agent-induced lipid droplet accumulation in a dose-dependent manner in MDA-MB-231 cells. This phenomenon was absent in MCF-7 cells and not evident when doxorubicin and apigenin were used concurrently, suggesting distinct cellular responses to these treatments that imply that their synergistic effects might be mediated through mechanisms unrelated to lipid metabolism. A further chemoinformatics analysis indicated that apigenin and doxorubicin might interact primarily at the level of ATP-binding cassette (ABC) transporter proteins, with potential indirect influences from the AKT and MYC signaling pathways. These results highlight the importance of understanding the nuanced interactions between apigenin and conventional chemotherapeutic drugs, as they could lead to more effective strategies for cancer treatment. This study underscores apigenin's potential as a modulator of cancer cell dynamics through mechanisms independent of its direct antioxidant effects, thereby contributing to the development of flavonoid-based adjunct therapies in cancer management.

Biomaterials in Cancer Therapy: Investigating the Interaction between Kaempferol and Zinc Ions through Computational, Spectroscopic and Biological Analyses.

A complex of the natural flavonoid kaempferol with zinc (Kam-Zn) was synthesized, and its physicochemical properties were investigated using spectroscopic methods such as Fourier transform infrared spectroscopy (FT-IR), ultraviolet-visible (UV-Vis) spectroscopy and theoretical chemistry. Biological studies were conducted to evaluate the cytotoxic and antiproliferative effects of these complexes on MCF-7 breast cancer cells. Treatment with Kam 100 µM (84.86 ± 7.79%; 64.37 ± 8.24%) and Kam-Zn 100 µM (91.87 ± 3.80%; 87.04 ± 13.0%) showed no significant difference in proliferation between 16 h and 32 h, with the gap width remaining stable. Both Kam-Zn 100 µM and 200 µM demonstrated effective antiproliferative and cytotoxic activity, significantly decreasing cell viability and causing cell death and morphology changes. Antioxidant assays revealed that Kam (IC50 = 5.63 ± 0.06) exhibited higher antioxidant potential compared to Kam-Zn (IC50 = 6.80 ± 0.075), suggesting that zinc coordination impacts the flavonoid's radical scavenging activity by the coordination of metal ion to hydroxyl groups. Computational studies revealed significant modifications in the electronic structure and properties of Kam upon forming 1:1 complexes with Zn2+ ions. Spectroscopy analyses confirmed structural changes, highlighting shifts in absorption peaks and alterations in functional group vibrations indicative of metal-ligand interactions. FT-IR and UV-Vis spectra analysis suggested that Zn coordinates with the 3-OH and 4C=O groups of ligand. These findings suggest that the Kam-Zn complex exhibits interesting antiproliferative, cytotoxic and modified antioxidant effects on MCF-7 cells, providing valuable insights into their structural and anticancer properties.

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.

The Influence of Lifestyle on Male Fertility in the Context of Insulin Resistance-Identification of Factors That Influence Semen Quality.

Background: Male fertility is known to have been negatively influenced by the progress of civilization. Another condition whose incidence has been on the increase for the same reason is insulin resistance (IR). In addition, men increasingly often resign from the pursuit of active forms of leisure, preferring more sedentary ones. Considering these trends, this aim of this study was to investigate the relationships between lifestyle factors, insulin resistance, and male fertility in men with and without the condition. A further aim was to select those lifestyle factors that would make it possible to predict the level of male fertility, especially when IR is concerned. Methods: This study was performed in a group of 73 participants, divided into groups based on their insulin resistance status. Their physical activity, diet, perceived stress, sleep quality, libido level, and duration of sexual abstinence were assessed on the basis of a number of parameters, including indices proposed by the authors. In addition, relevant anthropometric measurements were taken and tests related to glucose metabolism and semen quality were carried out. On the basis of these data, statistical tests were performed to establish or disprove relationships between lifestyle choices and semen quality, as measured my sperm motility. Results: The results of this study highlighted the associations between a number of parameters, i.e., micronutrient and vitamin intake, diet quality, body composition, insulin resistance, and the duration of sexual abstinence, and semen quality, as measured by sperm motility. Significantly, the presence or absence of IR was linked to male fertility. A multivariate model was developed, incorporating parameters such as the Matsuda index, vitamin intake, and sexual abstinence duration, to predict motility scores. Conclusions: This study underscores the negative impact of modern civilization's lifestyle choices on male fertility. Notably, vitamin and mineral consumption, especially from antioxidant-rich diets like the Mediterranean diet, emerged as key modifiable factors affecting fertility. Routine diagnostics for insulin resistance in fertility-related interventions is recommended. This study also highlights the importance of considering sexual abstinence duration during semen collection for accurate diagnostic results. Future research should focus on validating the proposed multivariate model and exploring the effects of lifestyle modifications, particularly vitamin supplementation, on fertility outcomes in men, especially in the context of IR.

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.

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.

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.

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.