Age-related shifts in mental health determinants from a deprived area in the European Union: informing the national healthy aging program of Hungary.

Mental disorders are among the leading causes of disability worldwide, disproportionately affecting older people. This study aims to assess the mental health of elderly individuals living in a deprived region of Hungary, and to identify and estimate the weight of different determinants of mental health across different age groups. A cross-sectional study was conducted with randomly selected samples of individuals (n = 860) aged 18 years and older in Northeast Hungary. The World Health Organization Well-Being Index (WHO-5), the single-item Life Satisfaction Scale, and the 12-item General Health Questionnaire (GHQ-12) were used to measure mental health of the participants. Multiple linear regression analysis was performed to measure the association between sociodemographic and health-related variables and mental health. Overall, the mean WHO-5 score was 69.2 ± 18.1 and it showed a significant decrease by age (p < 0.001), with the lowest score observed in aged 75 years and above (p < 0.001). The mean life satisfaction score was 7.5 ± 1.9 and it showed a significant decreasing trend over the life course (p < 0.001). The highest level of psychological distress as assessed by GHQ-12 was observed in the group aged 75 years or older (11.5 ± 6.0, p < 0.001). Multiple linear regression indicated that self-reported financial status, social support, sense of control over their health, activity limitation and pain intensity were the most important determinants of mental health among older adults. Interventions to improve the mental health of older adults should focus on the positive impact of social support, the reduction of financial insecurity and the use of effective pain relief medications.

Identification of Plasma Lipid Alterations Associated with Melanoma Metastasis.

The aim of this study was to apply a state-of-the-art quantitative lipidomic profiling platform to uncover lipid alterations predictive of melanoma progression. Our study included 151 melanoma patients; of these, 83 were without metastasis and 68 with metastases. Plasma samples were analyzed using a targeted Lipidyzer™ platform, covering 13 lipid classes and over 1100 lipid species. Following quality control filters, 802 lipid species were included in the subsequent analyses. Total plasma lipid contents were significantly reduced in patients with metastasis. Specifically, levels of two out of the thirteen lipid classes (free fatty acids (FFAs) and lactosylceramides (LCERs)) were significantly decreased in patients with metastasis. Three lipids (CE(12:0), FFA(24:1), and TAG47:2-FA16:1) were identified as more effective predictors of melanoma metastasis than the well-known markers LDH and S100B. Furthermore, the predictive value substantially improved upon combining the lipid markers. We observed an increase in the cumulative levels of five lysophosphatidylcholines (LPC(16:0); LPC(18:0); LPC(18:1); LPC(18:2); LPC(20:4)), each individually associated with an elevated risk of lymph node metastasis but not cutaneous or distant metastasis. Additionally, seventeen lipid molecules were linked to patient survival, four of which (CE(12:0), CE(14:0), CE(15:0), SM(14:0)) overlapped with the lipid panel predicting metastasis. This study represents the first comprehensive investigation of the plasma lipidome of melanoma patients to date. Our findings suggest that plasma lipid profiles may serve as important biomarkers for predicting clinical outcomes of melanoma patients, including the presence of metastasis, and may also serve as indicators of patient survival.

Genetic Background of Acute Heart Rate Response to Exercise.

The acute heart rate response (AHRR) to physical activity, which refers to the change in heart rate during and after exercise, has been associated with cardiovascular and all-cause mortality. Previous studies have shown that AHRR is significantly determined by genetics in addition to environmental and lifestyle factors. The aim of this study was to investigate the genetic background of AHRR by analysing ten single nucleotide polymorphisms (SNPs) associated with leisure-time physical activity (LTPA) in 620 samples from the Hungarian population. The AHRR can be characterised as the difference between post-exercise and resting heart rate, i.e., the delta heart rate (ΔHR) defined by the YMCA 3 min step test, with a lower value indicating better cardiovascular fitness. The association of SNPs with ΔHR was analysed both separately and in combination using an optimised polygenic score (oPGS). The results showed that five SNPs (rs10252228, rs459465, rs6022999, rs8097348, and rs12405556) had at least nominally significant (p < 0.05) individual associations with ΔHR. After optimizing the PGS, a cumulative effect was observed for eight SNPs (rs6022999, rs12405556, rs459465, rs10252228, rs8097348, rs10887741, rs12612420, and rs7023003) that had a strong and statistically significant association with ΔHR (B = -2.51, 95% CI: -3.46--1.76; p = 2.99 × 10-9). Of the four main domains of physical activity, the oPGS showed a significant positive association only with LTPA (B = 84.60; 95%CI: 25.23-143.98; p = 0.005). In conclusion, our results suggest that the SNPs we investigated influence individual leisure-time physical activity, mediated by their effects on the acute heart rate response.

Cross-sectional comparison of health care delivery and reimbursement between segregated and nonsegregated communities in Hungary.

Introduction: Spatially segregated, socio-economically deprived communities in Europe are at risk of being neglected in terms of health care. In Hungary, poor monitoring systems and poor knowledge on the health status of people in these segregated areas prevent the development of well-informed effective interventions for these vulnerable communities. Aims: We used data available from National Health Insurance Fund Management to better describe health care performance in segregated communities and to develop more robust monitoring systems. Methods: A cross-sectional study using 2020 health care data was conducted on each general medical practice (GMP) in Hungary providing care to both segregated and nonsegregated (complementary) adult patients. Segregated areas were mapped and ascertained by a governmental decree that defines them as within settlement clusters of adults with low level of education and income. Age, sex, and eligibility for exemption certificate standardized indicators for health care delivery, reimbursement, and premature mortality were computed for segregated and nonsegregated groups of adults and aggregated at the country level. The ratio of segregation and nonsegregation specific indicators (relative risk, RR) was computed with the corresponding 95% confidence intervals (95% CI). Results: Broad variations between GMPs were detected for each indicator. Segregated groups had a significantly higher rate of health care service use than complementary groups (RR = 1.22, 95% CI: 1.219;1.223) while suffering from significantly reduced health care reimbursement (RR = 0.940, 95% CI: 0.929;0.951). The risk of premature mortality was significantly higher among segregated patients (RR = 1.184, 95% CI: 1.087;1.289). Altogether, living in a segregated area led to an increase in visits to health care services by 18.1% with 6.6% less health spending. Conclusion: Adults living in segregated areas use health care services more frequently than those living in nonsegregated areas; however, the amount of health care reimbursement they receive is significantly lower, suggesting lower quality of care. The health status of segregated adults is remarkably lower, as evidenced by their higher premature mortality rate. These findings demonstrate the need for intervention in this vulnerable group. Because our study reveals serious variation across GMPs, segregation-specific monitoring is necessary to support programs sensitive to local issues and establish necessary benchmarks.

The Semmelweis Study: a longitudinal occupational cohort study within the framework of the Semmelweis Caring University Model Program for supporting healthy aging.

The Semmelweis Study is a prospective occupational cohort study that seeks to enroll all employees of Semmelweis University (Budapest, Hungary) aged 25 years and older, with a population of 8866 people, 70.5% of whom are women. The study builds on the successful experiences of the Whitehall II study and aims to investigate the complex relationships between lifestyle, environmental, and occupational risk factors, and the development and progression of chronic age-associated diseases. An important goal of the Semmelweis Study is to identify groups of people who are aging unsuccessfully and therefore have an increased risk of developing age-associated diseases. To achieve this, the study takes a multidisciplinary approach, collecting economic, social, psychological, cognitive, health, and biological data. The Semmelweis Study comprises a baseline data collection with open healthcare data linkage, followed by repeated data collection waves every 5 years. Data are collected through computer-assisted self-completed questionnaires, followed by a physical health examination, physiological measurements, and the assessment of biomarkers. This article provides a comprehensive overview of the Semmelweis Study, including its origin, context, objectives, design, relevance, and expected contributions.

Comparative analysis of health status and health service utilization patterns among rural and urban elderly populations in Hungary: a study on the challenges of unhealthy aging.

The demographic transition poses a significant challenge for health systems, especially in Central and Eastern European (CEE) countries, where the healthcare needs of aging populations are on the rise. This study aimed to describe and compare the health status and utilization of health services among the elderly residing in urban and rural areas of the most deprived region in Hungary. A comprehensive health survey was conducted in 2022, involving a randomly selected sample of 443 older adults (≥ 65 years) in Northeast Hungary. Multivariable logistic regression models adjusting for age, sex, education, financial status, chronic diseases, and activity limitations were used to investigate the association between type of residence and health service use. Among the study participants, 62.3% were female, 38.3% attained primary education, 12.5% reported a bad or very bad financial situation and 52.6% lived in urban areas. Overall, 24% of the elderly rated their health as very good or good (27.8% in urban and 19.7% in rural areas), while 57.8% (52.6% and 63.5% in urban and rural areas) reported limitations in daily activities. Compared to urban residents, rural residents reported lower rates of dentist visits (p = 0.006), specialist visits (p = 0.028), faecal occult blood testing (p < 0.001), colorectal cancer screening with colonoscopy (p = 0.014), and breast cancer screening (p = 0.035), and a higher rate of blood pressure measurement (p = 0.042). Multivariable models indicated that urban residence was positively associated with faecal occult blood testing (OR = 2.32, p = 0.014), but negatively associated with blood pressure (OR = 0.42, p = 0.017) and blood glucose measurements (OR = 0.48, p = 0.009). These findings highlight the influence of residence on health service utilization among older adults in Hungary. Further comprehensive studies are needed to better understand the health needs of the elderly population and to develop policies aimed at promoting healthy aging in CEE countries.

Association of HDL Subfraction Profile with the Progression of Insulin Resistance.

Type 2 diabetes mellitus (T2DM) is a major global public health problem, as it is associated with increased morbidity, mortality, and healthcare costs. Insulin resistance (IR) is a condition characterized by disturbances in carbohydrate and lipid metabolism that precedes T2DM. The aim of the present study was to investigate the association between HDL and its subfraction profile and the progression of IR, as assessed by the Homeostatic Model Assessment for IR (HOMA-IR) index, and to define cut-off values to identify an increased risk of IR. Individuals with a HOMA-IR greater than 3.63 were considered to have IR. The HDL subfractions were separated using the Lipoprint system, which identifies ten subfractions (HDL-1-10) in three subclasses as large (HDL-L), intermediate (HDL-I) and small (HDL-S). Analyses were performed on samples from 240 individuals without IR and 137 with IR from the Hungarian general and Roma populations. The HDL-1 to -6 subfractions and the HDL-L and -I classes showed a significant negative association with the progression and existence of IR. Among them, HDL-2 (B = -40.37, p = 2.08 × 10-11) and HDL-L (B = -14.85, p = 9.52 × 10-10) showed the strongest correlation. The optimal threshold was found to be 0.264 mmol/L for HDL-L and 0.102 mmol/L and above for HDL-2. Individuals with HDL-L levels below the reference value had a 5.1-fold higher risk of IR (p = 2.2 × 10-7), while those with HDL-2 levels had a 4.2-fold higher risk (p = 3.0 × 10-6). This study demonstrates that the HDL subfraction profile (especially the decrease in HDL-2 and -L) may be a useful marker for the early detection and intervention of atherogenic dyslipidemia in subjects with impaired glucose and insulin metabolism.

A combination of strongly associated prothrombotic single nucleotide polymorphisms could efficiently predict venous thrombosis risk.

Background: Venous thrombosis (VT) is multifactorial trait that contributes to the global burden of cardiovascular diseases. Although abundant single nucleotide polymorphisms (SNPs) provoke the susceptibility of an individual to VT, research has found that the five most strongly associated SNPs, namely, rs6025 (F5 Leiden), rs2066865 (FGG), rs2036914 (F11), rs8176719 (ABO), and rs1799963 (F2), play the greatest role. Association and risk prediction models are rarely established by using merely the five strongly associated SNPs. This study aims to explore the combined VT risk predictability of the five SNPs and well-known non-genetic VT risk factors such as aging and obesity in the Hungarian population. Methods: SNPs were genotyped in the VT group (n = 298) and control group (n = 400). Associations were established using standard genetic models. Genetic risk scores (GRS) [unweighted GRS (unGRS), weighted GRS (wGRS)] were also computed. Correspondingly, the areas under the receiver operating characteristic curves (AUCs) for genetic and non-genetic risk factors were estimated to explore their VT risk predictability in the study population. Results: rs6025 was the most prevalent VT risk allele in the Hungarian population. Its risk allele frequency was 3.52-fold higher in the VT group than that in the control group [adjusted odds ratio (AOR) = 3.52, 95% CI: 2.50-4.95]. Using all genetic models, we found that rs6025 and rs2036914 remained significantly associated with VT risk after multiple correction testing was performed. However, rs8176719 remained statistically significant only in the multiplicative (AOR = 1.33, 95% CI: 1.07-1.64) and genotypic models (AOR = 1.77, 95% CI: 1.14-2.73). In addition, rs2066865 lost its significant association with VT risk after multiple correction testing was performed. Conversely, the prothrombin mutation (rs1799963) did not show any significant association. The AUC of Leiden mutation (rs6025) showed better discriminative accuracy than that of other SNPs (AUC = 0.62, 95% CI: 0.57-0.66). The wGRS was a better predictor for VT than the unGRS (AUC = 0.67 vs. 0.65). Furthermore, combining genetic and non-genetic VT risk factors significantly increased the AUC to 0.89 with statistically significant differences (Z = 3.924, p < 0.0001). Conclusions: Our study revealed that the five strongly associated SNPs combined with non-genetic factors could efficiently predict individual VT risk susceptibility. The combined model was the best predictor of VT risk, so stratifying high-risk individuals based on their genetic profiling and well-known non-modifiable VT risk factors was important for the effective and efficient utilization of VT risk preventive and control measures. Furthermore, we urged further study that compares the VT risk predictability in the Hungarian population using the formerly discovered VT SNPs with the novel strongly associated VT SNPs.

Exposome and unhealthy aging: environmental drivers from air pollution to occupational exposures.

The aging population worldwide is facing a significant increase in age-related non-communicable diseases, including cardiovascular and brain pathologies. This comprehensive review paper delves into the impact of the exposome, which encompasses the totality of environmental exposures, on unhealthy aging. It explores how environmental factors contribute to the acceleration of aging processes, increase biological age, and facilitate the development and progression of a wide range of age-associated diseases. The impact of environmental factors on cognitive health and the development of chronic age-related diseases affecting the cardiovascular system and central nervous system is discussed, with a specific focus on Alzheimer's disease, Parkinson's disease, stroke, small vessel disease, and vascular cognitive impairment (VCI). Aging is a major risk factor for these diseases. Their pathogenesis involves cellular and molecular mechanisms of aging such as increased oxidative stress, impaired mitochondrial function, DNA damage, and inflammation and is influenced by environmental factors. Environmental toxicants, including ambient particulate matter, pesticides, heavy metals, and organic solvents, have been identified as significant contributors to cardiovascular and brain aging disorders. These toxicants can inflict both macro- and microvascular damage and many of them can also cross the blood-brain barrier, inducing neurotoxic effects, neuroinflammation, and neuronal dysfunction. In conclusion, environmental factors play a critical role in modulating cardiovascular and brain aging. A deeper understanding of how environmental toxicants exacerbate aging processes and contribute to the pathogenesis of neurodegenerative diseases, VCI, and dementia is crucial for the development of preventive strategies and interventions to promote cardiovascular, cerebrovascular, and brain health. By mitigating exposure to harmful environmental factors and promoting healthy aging, we can strive to reduce the burden of age-related cardiovascular and brain pathologies in the aging population.

Investigation of the relationship of general and digital health literacy with various health-related outcomes.

Background: Despite the growing number of health literacy surveys, we know little about the combined effect of the different dimensions of health literacy on various health-related outcomes. Objective: Thus, our study aimed to examine the impacts of general and digital health literacy on health behaviour, confidence in vaccination, self-perceived health, and health care utilization. Methods: Our research was part of the Health Literacy Population Survey 2019-2021, which was an international, multicentre, cross-sectional study. The data were collected via computer-assisted telephone interview in December 2020 in Hungary. Multiple multinomial logistic and multivariate linear regression models were used to analyse the separately effects of general and digital health literacy on the studied outcomes. Moreover, the combined effect of general and digital health literacy was also analysed via sensitivity analyses. In the last step, the interactions between general and digital health literacy were examined using the Johnson-Neyman procedure. Results: The results did not reveal any associations between health literacy and health behaviour. Health care use was only affected by digital health literacy; however, this effect was inconsistent. Both dimensions of health literacy were positively associated with self-perceived health and vaccination confidence. Conclusion: Our results suggest that increasing health literacy could promote health and vaccination confidence, while the potential effect of higher digital health literacy on more conscious use of the health care system should be investigated further.

Association of CETP Gene Polymorphisms and Haplotypes with Cardiovascular Risk.

Cholesteryl ester transfer protein (CETP) is known to influence HDL-C levels, potentially altering the profile of HDL subfractions and consequently cardiovascular risk (CVR). This study aimed to investigate the effect of five single-nucleotide polymorphisms (SNPs; rs1532624, rs5882, rs708272, rs7499892, and rs9989419) and their haplotypes (H) in the CETP gene on 10-year CVR estimated by the Systematic Coronary Risk Evaluation (SCORE), the Framingham Risk Score for Coronary Heart Disease (FRSCHD) and Cardiovascular Disease (FRSCVD) algorithms. Adjusted linear and logistic regression analyses were used to investigate the association of SNPs and 10 haplotypes (H1-H10) on 368 samples from the Hungarian general and Roma populations. The T allele of rs7499892 showed a significant association with increased CVR estimated by FRS. H5, H7, and H8 showed a significant association with increased CVR based on at least one of the algorithms. The impact of H5 was due to its effect on TG and HDL-C levels, while H7 showed a significant association with FRSCHD and H8 with FRSCVD mediated by a mechanism affecting neither TG nor HDL-C levels. Our results suggest that polymorphisms in the CETP gene may have a significant effect on CVR and that this is not mediated exclusively by their effect on TG and HDL-C levels but also by presently unknown mechanisms.

Lung cancer multi-omics digital human avatars for integrating precision medicine into clinical practice: the LANTERN study.

BACKGROUND: The current management of lung cancer patients has reached a high level of complexity. Indeed, besides the traditional clinical variables (e.g., age, sex, TNM stage), new omics data have recently been introduced in clinical practice, thereby making more complex the decision-making process. With the advent of Artificial intelligence (AI) techniques, various omics datasets may be used to create more accurate predictive models paving the way for a better care in lung cancer patients. METHODS: The LANTERN study is a multi-center observational clinical trial involving a multidisciplinary consortium of five institutions from different European countries. The aim of this trial is to develop accurate several predictive models for lung cancer patients, through the creation of Digital Human Avatars (DHA), defined as digital representations of patients using various omics-based variables and integrating well-established clinical factors with genomic data, quantitative imaging data etc. A total of 600 lung cancer patients will be prospectively enrolled by the recruiting centers and multi-omics data will be collected. Data will then be modelled and parameterized in an experimental context of cutting-edge big data analysis. All data variables will be recorded according to a shared common ontology based on variable-specific domains in order to enhance their direct actionability. An exploratory analysis will then initiate the biomarker identification process. The second phase of the project will focus on creating multiple multivariate models trained though advanced machine learning (ML) and AI techniques for the specific areas of interest. Finally, the developed models will be validated in order to test their robustness, transferability and generalizability, leading to the development of the DHA. All the potential clinical and scientific stakeholders will be involved in the DHA development process. The main goals aim of LANTERN project are: i) To develop predictive models for lung cancer diagnosis and histological characterization; (ii) to set up personalized predictive models for individual-specific treatments; iii) to enable feedback data loops for preventive healthcare strategies and quality of life management. DISCUSSION: The LANTERN project will develop a predictive platform based on integration of multi-omics data. This will enhance the generation of important and valuable information assets, in order to identify new biomarkers that can be used for early detection, improved tumor diagnosis and personalization of treatment protocols. ETHICS COMMITTEE APPROVAL NUMBER: 5420 - 0002485/23 from Fondazione Policlinico Universitario Agostino Gemelli IRCCS - Università Cattolica del Sacro Cuore Ethics Committee. TRIAL REGISTRATION: clinicaltrial.gov - NCT05802771.

Comparison of Genetic Susceptibility to Coronary Heart Disease in the Hungarian Populations: Risk Prediction Models for Coronary Heart Disease.

Background and Aim: It was evaluated whether the integration of genetic risk scores (GRS-unweighted, wGRS-weighted) into conventional risk factor (CRF) models for coronary heart disease or acute myocardial infarction (CHD/AMI) could improve the predictive ability of the models. Methods: Subjects and data collected in a previous survey were used to perform regression and ROC curve analyses as well as to examine the role of genetic components. Thirty SNPs were selected, and genotype and phenotype data were available for 558 participants (general: N = 279 and Roma: N = 279). Results: The mean GRS (27.27 ± 3.43 vs. 26.68 ± 3.51, p = 0.046) and wGRS (3.52 ± 0.68 vs. 3.33 ± 0.62, p = 0.001) were significantly higher in the general population. The addition of the wGRS to the CRF model yielded the strongest improvement in discrimination among Roma (from 0.8616 to 0.8674), while the addition of GRS to the CRF model yielded the strongest improvement in discrimination in the general population (from 0.8149 to 0.8160). In addition to that, the Roma individuals were likely to develop CHD/AMI at a younger age than subjects in the general population. Conclusions: The combination of the CRFs and genetic components improved the model's performance and predicted AMI/CHD better than CRFs alone.

Heavy metals in unrecorded Albanian rakia: A pilot study on a potential public health risk.

Unrecorded alcohol has been linked to illness above and beyond that caused by ethanol alone because of the presence of toxic contaminants. While it can be found in all countries, consumption is high in Albania, where it is frequently consumed as a fruit brandy known as rakia. Among the contaminants identified previously in such products, metals including lead have been detected at levels posing a risk to health but there is little information on their presence in rakia. To fill this gap, we measured the level of ethanol and 24 elements among them toxic metals in 30 Albanian rakia samples. We found that 63.3% of rakia samples had ethanol concentration above 40% v/v. We also showed that there was a significant difference between the measured [mean: 46.7% v/v, interquartile range (IQR): 43.4-52.1% v/v] and reported (mean: 18.9% v/v, IQR: 17.0-20.0% v/v) concentrations of ethanol in rakia. Among the metals detected, aluminium, copper, iron, manganese, lead, and zinc were present in rakia samples at concentrations ranging between 0.013 and 0.866 mg/l of pure alcohol (pa), 0.025-31.629 mg/l of pa, 0.004-1.173 mg/l of pa, 0.185-45.244 mg/l of pa, 0.044-1.337 mg/l of pa, and 0.004-10.156 mg/l of pa, respectively. Copper and lead were found to be the greatest concern posing a potential public health risk. Although the estimated daily intake of these heavy metals from unrecorded rakia was below their toxicological threshold, the concentrations of lead and copper exceeded their limit value of 0.2 and 2.0 mg/l of pa specified for spirits in 33% and 90% of samples, respectively. Therefore, the possibility of adverse health effects cannot be excluded completely. Our findings highlight the need for action by policymakers against the risks posed by these products in Albania.

Genetic Determinants of Leisure-Time Physical Activity in the Hungarian General and Roma Populations.

Leisure-time physical activity (LTPA) is one of the modifiable lifestyle factors that play an important role in the prevention of non-communicable (especially cardiovascular) diseases. Certain genetic factors predisposing to LTPA have been previously described, but their effects and applicability on different ethnicities are unknown. Our present study aims to investigate the genetic background of LTPA using seven single nucleotide polymorphisms (SNPs) in a sample of 330 individuals from the Hungarian general (HG) and 314 from the Roma population. The LTPA in general and three intensity categories of it (vigorous, moderate, and walking) were examined as binary outcome variables. Allele frequencies were determined, individual correlations of SNPs to LTPA, in general, were determined, and an optimized polygenetic score (oPGS) was created. Our results showed that the allele frequencies of four SNPs differed significantly between the two study groups. The C allele of rs10887741 showed a significant positive correlation with LTPA in general (OR = 1.48, 95% CI: 1.12-1.97; p = 0.006). Three SNPs (rs10887741, rs6022999, and rs7023003) were identified by the process of PGS optimization, whose cumulative effect shows a strong significant positive association with LTPA in general (OR = 1.40, 95% CI: 1.16-1.70; p < 0.001). The oPGS showed a significantly lower value in the Roma population compared with the HG population (oPGSRoma: 2.19 ± SD: 0.99 vs. oPGSHG: 2.70 ± SD: 1.06; p < 0.001). In conclusion, the coexistence of genetic factors that encourage leisure-time physical activity shows a more unfavorable picture among Roma, which may indirectly contribute to their poor health status.

Genetic Background of Metabolically Healthy and Unhealthy Obesity Phenotypes in Hungarian Adult Sample Population.

A specific phenotypic variant of obesity is metabolically healthy (MHO), which is characterized by normal blood pressure and lipid and glucose profiles, in contrast to the metabolically unhealthy variant (MUO). The genetic causes underlying the differences between these phenotypes are not yet clear. This study aims to explore the differences between MHO and MUO and the contribution of genetic factors (single nucleotide polymorphisms-SNPs) in 398 Hungarian adults (81 MHO and 317 MUO). For this investigation, an optimized genetic risk score (oGRS) was calculated using 67 SNPs (related to obesity and to lipid and glucose metabolism). Nineteen SNPs were identified whose combined effect was strongly associated with an increased risk of MUO (OR = 1.77, p < 0.001). Four of them (rs10838687 in MADD, rs693 in APOB, rs1111875 in HHEX, and rs2000813 in LIPG) significantly increased the risk of MUO (OR = 1.76, p < 0.001). Genetic risk groups based on oGRS were significantly associated with the risk of developing MUO at a younger age. We have identified a cluster of SNPs that contribute to the development of the metabolically unhealthy phenotype among Hungarian adults suffering from obesity. Our findings emphasize the significance of considering the combined effect(s) of multiple genes and SNPs in ascertaining cardiometabolic risk in obesity in future genetic screening programs.

Taste Preference-Related Genetic Polymorphisms Modify Alcohol Consumption Behavior of the Hungarian General and Roma Populations.

Harmful alcohol consumption has been considered a major public health issue globally, with the amounts of alcohol drunk being highest in the WHO European Region including Hungary. Alcohol consumption behaviors are complex human traits influenced by environmental factors and numerous genes. Beyond alcohol metabolization and neurotransmitter gene polymorphisms, taste preference-related genetic variants may also mediate alcohol consumption behaviors. Applying the Alcohol Use Disorders Identification Test (AUDIT) we aimed to elucidate the underlying genetic determinants of alcohol consumption patterns considering taste preference gene polymorphisms (TAS1R3 rs307355, TAS2R38 rs713598, TAS2R19 rs10772420 and CA6 rs2274333) in the Hungarian general (HG) and Roma (HR) populations. Alcohol consumption assessment was available for 410 HG and 387 HR individuals with 405 HG and 364 HR DNA samples being obtained for genotyping. No significant associations were found between TAS1R3 rs307355, TAS2R19 rs10772420, and CA6 rs2274333 polymorphisms and alcohol consumption phenotypes. Significant associations were identified between TAS2R38 rs713598 and the number of standard drinks consumed in the HG sample (genotype GG negatively correlated with the number of standard drinks; coef: -0.136, p = 0.028) and the prevalence of having six or more drinks among Roma (a negative correlation was identified in the recessive model; genotype GG, coef: -0.170, p = 0.049), although, none of these findings passed the Bonferroni-corrected probability criterion (p > 0.05). Nevertheless, our findings may suggest that alcohol consumption is partially driven by genetically determined taste preferences in our study populations. Further studies are required to strengthen the findings and to understand the drivers of alcohol consumption behavior in more depth.

Identification of liquid biopsy-based mutations in colorectal cancer by targeted sequencing assays.

Recently, liquid biopsy, as a promising approach was introduced for the analysis of different tumor-derived circulating markers including tumor DNA and cell free DNA (ct/cfDNA). Identification of mutations in cfDNA may allow the early detection of tumors, as well as predicting and monitoring treatment responses in a minimally invasive way. In the present study, we used commercially available gene panels to verify the mutation overlap between liquid biopsy and abnormalities detected in colorectal tumor tissue. The two panels (Archer®VariantPlex®Solid Tumor and LIQUIDPlexTM ctDNA) overlap in 23 genes, which enables a comprehensive view of tumor-plasma mutational status by next generation sequencing. We successfully analyzed 16 plasma and 16 tumor samples. We found that 87% of tumor tissues contained 44 mutations in 12 genes and 43.8% of cfDNA harbored 13 mutations in 5 genes. To verify whether the mutation pattern of the tumor DNA could be consistently detected in plasma cfDNA, we compared the alterations between cfDNA and matched tissue DNA in nine patients. Six of the 9 tumor tissues harbored mutations in TP53, KRAS or MET genes, those were not detectable by the ctDNA kit, even eventhough the exons of these genes overlap in both panels. Comparing the mutational patterns of the matched samples, we found that only one cfDNA had the same mutations (KRAS, SMAD4 and TP53) in the paired tissue. The results of the comparison between tumor tissue DNA and matched plasma cfDNA underline the importance of studying the paired solid tumor and plasma samples together.