Cost-effectiveness of population-wide genomic screening for Lynch Syndrome and Polygenic Risk Scores to inform Colorectal Cancer screening.

INTRODUCTION: Genomic screening to identify individuals with Lynch Syndrome (LS) and those with a high polygenic risk score (PRS) promises to personalize Colorectal Cancer (CRC) screening. Understanding its clinical and economic impact is needed to inform screening guidelines and reimbursement policies. METHODS: We developed a Markov model to simulate individuals over a lifetime. We compared LS+PRS genomic screening to standard of care (SOC) for a cohort of US adults at age 30. The Markov model included health states of "no CRC", CRC stages (A-D) and death. We estimated incidence, mortality, and discounted economic outcomes of the population under different interventions. RESULTS: Screening 1000 individuals for LS+PRS resulted in 1.36 fewer CRC cases and 0.65 fewer deaths compared to SOC. The incremental cost-effectiveness ratio (ICER) was $124,415 per quality-adjusted life-year (QALY); screening had a 69% probability of being cost-effective using a willingness to pay threshold of $150,000/QALY. Setting the PRS threshold at the 90th percentile of the LS+PRS screening program to define individuals at high risk was most likely to be cost-effective compared to 95th, 85th, and 80th percentiles. CONCLUSION: Population-level LS+PRS screening is marginally cost-effective and a threshold of 90th percentile is more likely to be cost-effective than other thresholds.

Long-term monitoring and treatment of venous thromboembolic disease: recommendations of the Thromboembolic Disease Group of the Spanish Society of Internal Medicine 2024.

Venous thromboembolim (VTE) is a highly prevalent condition that requires long-term monitoring and treatment. This monitoring includes: 1) completing the etiological study and determining the risk of VTE recurrence; 2) establishing the optimal duration of anticoagulant treatment, as well as the type of therapy and its dosage; 3) estimating the risk of bleeding, and 4) identifying the occurrence of chronic complications. This consensus document, prepared by the VTE Group of the Spanish Society of Internal Medicine (SEMI), aims to update and establish consensus recommendations on these aspects. The document focuses on four aspects of management: the first includes risk factors for VTE recurrence after an unprovoked VTE episode and describes the predictive scores of VTE recurrence; the second focuses on risk factors for bleeding; the third provides recommendations for long-term follow-up in VTE, addressing specific considerations for screening chronic thromboembolic pulmonary hypertension and post-thrombotic syndrome of the lower limbs; and the fourth provides guidance on the optimal duration of extended anticoagulant treatment, as well as the type of therapy and its dosage;. For each area, an exhaustive literature review was conducted, analyzing the updated VTE clinical guidelines and recent studies. This document is intended to be a guide in the long-term management of VTE based on the most current knowledge.

Interactive effects of genetic liability and combat exposure on risk of alcohol use disorder among US service members.

BACKGROUND: An improved understanding of pathways to alcohol use disorder (AUD) among service members may inform efforts to reduce the substantial impact of AUD on this population. This study examined whether the relationship between a service-related risk factor (combat exposure) and later AUD varied based on individual differences in genetic liability to AUD. METHODS: The sample consisted of 1203 US Army soldiers of genetically determined European ancestry who provided survey and genomic data in the Army STARRS Pre/Post Deployment Study (PPDS; 2012-2014) and follow-up survey data in wave 1 of the STARRS Longitudinal Study (2016-2018). Logistic regression was used to estimate the conditional effect of combat exposure level (self-reported in PPDS) on odds of probable AUD diagnosis at follow-up, as a function of a soldier's polygenic risk score (PRS) for AUD. RESULTS: The direct effect of combat exposure on AUD risk was non-significant (AOR=1.12, 95 % CI=1.00-1.26, p=.051); however, a significant combat exposure x PRS interaction was observed (AOR=1.60, 95 % CI=1.03-2.46, p=.033). Higher combat exposure was more strongly associated with elevated AUD risk among soldiers with heightened genetic liability to AUD. CONCLUSIONS: The effect of combat exposure on AUD risk appeared to vary based on a service member's level of genetic risk for AUD. Continued investigation is warranted to determine whether PRS can help stratify AUD risk within stress-exposed groups such as combat-deployed soldiers. Such efforts might reveal opportunities to focus prevention efforts on smaller subgroups at the intersection of having both environmental exposures and genetic vulnerability to AUD.

The efficacy of different biomarkers and endpoints to refine referrals for suspected prostate cancer: the TARGET study (Tiered integrAted tests for eaRly diaGnosis of clinically significant ProstatE Tumours).

BACKGROUND: The majority of men referred with a raised PSA for suspected prostate cancer will receive unnecessary tertiary investigations including MRI and biopsy. Here, we compared different types of biomarkers to refine tertiary referrals and when different definitions of clinically significant cancer were used. METHODS: Data and samples from 798 men referred for a raised PSA (≥ 3 ng/mL) and investigated through an MRI-guided biopsy pathway were accessed for this study. Bloods were acquired pre-biopsy for liquid biomarkers and germline DNA. Variables explored included PSA + Age (base model), free/total PSA (FTPSA), Prostate Health Index (phi), PSA density (PSAd), polygenic risk score (PRS) and MRI (≥ LIKERT 3). Different diagnostic endpoints for significant cancer (≥ grade group 2 [GG2], ≥ GG3, ≥ Cambridge Prognostic Group 2 [CPG2], ≥ CPG3) were tested. The added value of each biomarker to the base model was evaluated using logistic regression models, AUC and decision curve analysis (DCA) plots. RESULTS: The median age and PSA was 65 years and 7.13 ng/mL respectively. Depending on definition of clinical significance, ≥ grade group 2 (GG2) was detected in 57.0% (455/798), ≥ GG3 in 27.5% (220/798), ≥ CPG2 in 61.6% (492/798) and ≥ CPG3 in 42.6% (340/798). In the pre-MRI context, the PSA + Age (base model) AUC for prediction of ≥ GG2, ≥ GG3, ≥ CPG2 and ≥ CPG3 was 0.66, 0.68, 0.70 and 0.75 respectively. Adding phi and PSAd to base model improved performance across all diagnostic endpoints but was notably better when the composite CPG prognostic score was used: AUC 0.82, 0.82, 0.83, 0.82 and AUC 0.74, 0.73, 0.79, 0.79 respectively. In contrast, neither FTPSA or PRS scores improved performance especially in detection of ≥ GG3 and ≥ CPG3 disease. Combining biomarkers did not alter results. Models using phi and PSAd post-MRI also improved performances but again benefit varied with diagnostic endpoint. In DCA analysis, models which incorporated PSAd and phi in particular were effective at reducing use of MRI and/or biopsies especially for ≥ CPG3 disease. CONCLUSION: Incorporating phi or PSAd can refine and tier who is referred for tertiary imaging and/or biopsy after a raised PSA test. Incremental value however varied depending on the definition of clinical significance and was particularly useful when composite prognostic endpoints are used.

Association between polygenic risk scores combined with clinical characteristics and antidepressant efficacy.

BACKGROUND: While millions of people suffer from major depressive disorder (MDD), research has shown that individual differences in antidepressant efficacy exist, potentially attributable to various factors. Polygenic risk scores (PRSs) carry clinical potential, but associations with treatment response are seldom reported. Here, we examined whether PRSs for MDD and schizophrenia (SCZ) are associated with antidepressant effectiveness and the influence of other factors. METHODS: A total of 999 patients were included, and the PRSs for the MDD and SCZ were calculated. The main outcome was a change in the 17-item Hamilton Depression Rating Scale (HAMD17) scores from before to after 2-week treatment. The Mann-Whitney test, Spearman correlation analysis, multiple stepwise linear regression analysis, and interaction analysis were used for statistical analysis. RESULTS: In the 912 subjects passing quality control, a difference in the HAM-D17 score reduction rate between the MDD phenotype PRS (MDD-PRS) high-risk and the low-risk groups was discovered (P = 0.009), and a correlation was found between the MDD-PRS and the HAM-D17 score reduction rate (r = -0.075, P = 0.024). Moreover, antidepressant efficacy was related to MDD-PRS (ß = -4.086, P = 0.039), the Snaith-Hamilton Pleasure Scale-total score (ß = -0.009, P = 0.005), and non-first episode (ß = -0.039, P < 0.001). However, the result of the interaction analysis was nonsignificant. LIMITATIONS: The main limitation was that only 1309 targeted genes were selected based on pathways known to be involved in MDD and/or antidepressant effects. CONCLUSION: These findings suggest a difference in antidepressant efficacy between patients in different MDD-PRS groups. Moreover, the MDD-PRS combined with clinical characteristics partially explained inter-individual differences in antidepressant efficacy.

Comparison of homocysteine, vitamin B12 and folic acid between rural and urban ageing Indians and its association with mild cognitive impairment and cardiovascular risk factors: a cross-sectional analysis.

The relationship between blood levels of homocysteine (HCY), vitamin B12, folic acid and cognitive impairment is inconclusive. Since HCY is an independent risk factor for cardiovascular diseases, understanding its association with Framingham risk score (FRS) may provide insight into the shared underlying mechanism between cardiovascular disease and cognitive impairment. Cross-sectional analyses utilized baseline data from two ongoing longitudinal studies: the Tata Longitudinal Study of Ageing (n = 923), an urban cohort, and Srinivaspura Ageing, NeuroSenescence and COGnition (n = 4239), a rural cohort. The study compared the HCY, vitamin B12 and folic acid levels across cohorts and normal versus mild cognitive impairment (MCI) participants. The association between HCY and cognitive status was established using regression models. Three models were analysed: model 1-unadjusted; model 2-adjusted for age, gender, smoking, alcohol consumption, diet, hypertension, cardiac illness, diabetes; and model 3-adjusted for variables in model 2 plus vitamin B12 and folic acid. Correlation was calculated between HCY and FRS. The urban cohort exhibited a significantly higher level of HCY [median (IQR) (17.70 (10.2) versus 14.70 (9.7); P < 0.001)], vitamin B12 (251 (231) versus 219 (138); P < 0.001) and folic acid (8.21 (8) versus 5.48 (4); P < 0.001) levels compared to rural cohort. HCY, vitamin B12 and folic acid levels did not differ significantly between normal and MCI participants in the urban cohort. In the rural cohort, among the age-gender matched MCI-normal, participants with normal cognition had higher levels of vitamin B12 (≥60 years) [227 (152) versus 217 (175); P = 0.03] and folic acid (<60 years) [5.91 (4) versus 5.40 (4); P = 0.04] compared to MCI. There was no association between HCY and cognitive status in both the cohorts, but there was a significant positive relationship between vitamin B12 deficiency and Clinical Dementia Rating-Sum of the Boxes (CDR-SOB), as well as folic acid deficiency and CDR-SOB in rural and urban cohorts, respectively, within a specific age group. A significant correlation was observed between FRS and HCY in the rural cohort (r = 0.17, P < 0.001), but not in the urban cohort. This study revealed significant differences in HCY, vitamin B12 and folic acid levels between the cohorts. In the rural cohort, participants with MCI had lower vitamin B12 and folic acid levels in a certain age group. Association between HCY and cognitive status was insignificant in both the cohorts. A small significant correlation between FRS and HCY was seen in the rural cohort.

Prevalence of Major Risk Factors and Assessment of 10-Year Risk for Cardiovascular Diseases Among Adults in Yaoundé, Cameroon: A Cross-Sectional Study.

Objective This study aimed to assess the prevalence of major risk factors for cardiovascular disease and the 10-year cardiovascular risk in an adult population residing in Yaoundé, Cameroon. Methodology We conducted a cross-sectional survey in 10 purposively selected neighbourhoods of Yaoundé, involving one adult per household who consented to participate. We collected data on personal and family history, lifestyle and nutritional habits, anthropometric parameters, and blood pressure, and calculated prevalence rates with 95% CI. Results The study involved 411 participants (172 males) with a median age of 28 years (IQR 23-40 years). Prevalence of CVD risk factors in our study population were family history of heart attack (4.4%; 95% CI 2.8-6.8%), stroke (7.5%; 95% CI 5.3-10.5%), harmful alcohol consumption (40.4%; 95% CI 35.8-45.3%), current smoking (5.1%; 95% CI 3.3-7.7%), second-hand smoking (26.6%; 95% CI 22.6-31.1%), low physical activity (66.4; 95% CI 61.7- 70.8%), inadequate fruit/vegetable intake (36.6%; 95% CI 31.4-42.1%), self-reported anxiety (83.5%; 95% CI 79.6-86.8%) and depression (52.3%; 95% CI 47.4-57.1%), overweight (27.0%, 95% CI 22.9 to 31.5%), obesity (25.1%, 95% CI 21.1 to 29.5%), abdominal obesity (65.9%; 95% CI 61.1-70.2%), excess body fat (46.3%; 95% CI 41.4-51.1%), suspected prehypertension (58.3%; 95% CI 51.1-65%) and hypertension (41.8%; 95% CI 35-48.9%). Furthermore, 40% of overall participants had a moderate-to-high 10-year CVD risk. Independent factors such as a personal history of other chronic diseases and parental history of either diabetes or hypertension combined with behaviours like harmful alcohol consumption and mean blood pressure might significantly influence the cardiovascular risk of our study population Conclusion In Yaoundé, Cameroon, many adults have major risk factors for cardiovascular disease, with nearly one-third of young adults at moderate to high risk of developing CVD within the next decade. Thus, it is crucial to implement targeted interventions to mitigate the risk of CVD.

A review of the advances in understanding the genetic basis of spondylarthritis and emerging clinical benefit.

Spondyloarthropathies (SpA), including ankylosing spondylitis (AS) and psoriatic arthritis (PsA), have been shown to have a substantial genetic predisposition based on heritability estimates derived from family studies and genome-wide association studies (GWAS). GWAS have uncovered numerous genetic loci associated with susceptibility to SpA, with significant associations to human leukocyte antigen (HLA) genes, which are major genetic risk factors for both AS and PsA. Specific loci differentiating PsA from cutaneous-only psoriasis have been identified, though these remain limited. Further research with larger sample sizes is necessary to identify more PsA-specific genetic markers. Current research focuses on translating these genetic insights into clinical applications. For example, polygenic risk scores are showing promise for the classification of disease risk and diagnosis and future research should focus on refining these risk assessment tools to improve clinical outcomes for individuals with SpA. Addressing these challenges will help integrate genetic testing into patients care and impact clinical practice.

Risk scores predicting disease progression in early-stage CLL: Comparative analysis and usefulness of IGHV subset #2 to improve their accuracy.

BACKGROUND: Overall, the prognosis of patients with chronic lymphocytic leukemia (CLL) in the early phase of the disease (Rai 0, Binet A) is favorable; some patients never require therapy. However, some patients require intervention shortly after diagnosis. In the past decade, several risk scores (RS) have been developed to predict disease progression, yet some patients are misclassified. On the other hand, IGHV subset 2 (IGHV2) predicts poor outcomes. METHODS: A retrospective and multicentric study was conducted to compare the accuracy of five different RS (IPS-E, CR0, AIPS-E, CLL-IPI, and Barcelona-Brno) to predict disease progression in 781 stage A previously untreated patients with CLL. As an exploratory analysis, it was further investigated whether the inclusion of the IGHV2 as a poor prognostic parameter improved the accuracy of RS. RESULTS: All the scores identified a similar group of patients with CLL in early stage with low-, intermediate-, and high-risk progression. Discrimination was high and similar in all RS (c-index = 0.74-0.79, area under the curve = 0.7-0.75), as well as calibration (p = .98) and parsimony, although CLL-IPI showed the best results (Akaike information criterion = 441). A total of 34.4% of patients were categorized within the same RS and concordance was at least moderate between RS. CONCLUSION: Moreover, the results suggest that IGHV2 may improve the accuracy of RS.

Healthcare professionals' knowledge and attitudes towards polygenic risk testing for glaucoma.

BACKGROUND: Effective clinical implementation of polygenic risk testing for glaucoma relies on healthcare professionals' attitudes and knowledge of the test. Given the emerging applications of the test, it will likely impact a range of healthcare professionals and will require competency in polygenic risk scores concepts for all those involved in patient care. To our knowledge, this is the first study to assess healthcare professionals' views towards polygenic testing for glaucoma. METHODS: An online cross-sectional questionnaire was distributed to healthcare professionals via relevant professional organisations in Australia. The questionnaire assessed experience and confidence with genetic testing, glaucoma and genetic knowledge, recommendations for the tests, and factors affecting the decision. RESULTS: A total of 94 participants completed the questionnaire. The sample was composed of ophthalmologists (36%), optometrists (21%), orthoptists (17%), general practitioners (16%) and clinical geneticists/genetic counsellors (10%). Although familiarity with polygenic risk scores for glaucoma was low overall (11%), the majority reported a positive attitude towards recommending testing based on known risk factors such as family history (91%) and older age (57%). Over 95% indicated that ophthalmologists would be the most appropriate group to order polygenic risk testing and communicate results. The majority felt they would benefit from more training on polygenic risk scores (93%). CONCLUSIONS: Our findings indicated that multiple groups of healthcare professionals were neither familiar nor confident with the concept of glaucoma polygenic risk testing, and identified training and education needs to support the implementation of testing into clinical practice.

Constructing and validating pan-apoptosis-related features for predicting prognosis and immunotherapy response in hepatocellular carcinoma.

The study aimed to develop a prognostic model for Hepatocellular Carcinoma (HCC) based on pan-apoptosis-related genes, a novel inflammatory programmed cell death form intricately linked to HCC progression. Utilizing transcriptome sequencing and clinical data from the TCGA database, we identified six crucial pan-apoptosis-related genes through statistical analyses. These genes were then employed to construct a prognostic model that accurately predicts overall survival rates in HCC patients. Our findings revealed a strong correlation between the model's risk scores and tumor microenvironment (TME) status, immune cell infiltration, and immune checkpoint expression. Furthermore, we screened for drugs with potential therapeutic efficacy in high- and low-risk HCC groups. Notably, PPP2R5B gene knockdown was found to inhibit HCC cell proliferation and clonogenic capacity, suggesting its role in HCC progression. In conclusion, this study presents a novel pan-apoptosis gene-based prognostic risk model for HCC, providing valuable insights into patient TME status and guiding the selection of targeted therapies and immunotherapies.

Descriptives and genetic correlates of eating disorder diagnostic transitions and presumed remission in the Danish registry.

Objective: Eating disorders (EDs) are serious psychiatric disorders with an estimated 3.3 million healthy life-years lost worldwide yearly. Understanding the course of illness, diagnostic transitions and remission, and their associated genetic correlates could inform both ED etiology and treatment. The authors investigated occurrences of ED transitions and presumed remission and their genetic correlates as captured by polygenic scores (PGSs) in a large Danish register-based cohort. Methods: The sample compromised of 10,565 individuals with a diagnosis of anorexia nervosa (AN), bulimia nervosa (BN), or eating disorder not otherwise specified (EDNOS) with at least two registered hospital contacts between 1995 and 2018. Based on medical records, occurrence of diagnostic transitions and periods of presumed remission were identified. Associations between 422 PGS and diagnostic transitions and presumed remission were evaluated using Cox proportional hazard models. Results: A minority of ED cases (14.1%-23.1%) experienced a diagnostic transition. Presumed remission ranged between 86.9%-89.8%. Higher (one SD increase) PGS for major depressive disorder and multisite chronic pain were positively associated with transitioning from AN to either BN or EDNOS. Higher PGS on a measure of body fat percentage and financial difficulties were positively associated with presumed remission from AN. Higher PGS for mood swings was positively associated with presumed remission from EDNOS whereas higher PGS for health rating showed the opposite. Conclusions: The authors found that most ED patients did not experience diagnostic transitions but were more likely to experience a period of presumed remission. Both diagnostic transitions and presumed remission have significant polygenic component.

Identification of Sweetness Preference-Related Single-Nucleotide Polymorphisms for Polygenic Risk Scores Associated with Obesity.

Our study aimed to identify sweetness preference-associated single-nucleotide polymorphisms (SNPs), characterize the related genetic loci, and develop SNP-based polygenic risk scores (PRS) to analyze their associations with obesity. For genotyping, we utilized a pooled genome-wide association study (GWAS) dataset of 18,499 females and 10,878 males. We conducted genome-wide association analyses, functional annotation, and employed the weighted method to calculate the levels of PRS from 677 sweetness preference-related SNPs. We used Cox proportional hazards modeling with time-varying covariates to estimate age-adjusted and multivariable hazard ratios (HRs) and 95% confidence intervals (CIs) for obesity incidence. We also tested the correlation between PRS and environmental factors, including smoking and dietary components, on obesity. Our results showed that in males, the TT genotype of rs4861982 significantly increased obesity risk compared to the GG genotype in the Health Professionals Follow-up Study (HPFS) cohort (HR = 1.565; 95% CI, 1.122-2.184; p = 0.008) and in the pooled analysis (HR = 1.259; 95% CI, 1.030-1.540; p = 0.025). Protein tyrosine phosphatase receptor type O (PTPRO) was identified as strongly associated with sweetness preference, indicating a positive correlation between sweetness preference and obesity risk. Moreover, each 10 pack-year increment in smoking was significantly associated with an increased risk of obesity in the HPFS cohort (HR = 1.024; 95% CI, 1.000-1.048) in males but not in females. In conclusion, significant associations between rs4861982, sweetness preference, and obesity were identified, particularly among males, where environmental factors like smoking are also correlated with obesity risk.

Comparison of five scores to predict mortality in malignant pleural effusion.

Malignant pleural effusion (MPE) is a complication of malignancy. Treatment of MPE is based on predicted outcome. The aim of this study was to compare the performance characteristics of LENT, PROMISE, RECLS, AL and pNLR scores for prediction of mortality in lung cancer patients who have MPE. Patients who were diagnosed with MPE that was associated with underlying lung cancer between January 2010 and December 2019 were included and analyzed retrospectively in a single center. Outcomes considered were 30-day, 6 months, and 1-year mortality. A total of 180 patients were examined. For 30-day mortality, the areas under the ROC curves (AUC) (95% CI) were: LENT 0.83 (0.76-0.87), RECLS 0.71 (0.63-0.77), and PROMISE 0.70 (0.17-0.38). For 6-month and 1-year mortality the order of these AUCs was similar. Cox regression showed that none of the scores were significantly associated with 30-day mortality, but LENT and RECLS were significantly associated with 6-month and 1-year mortality. Comparison of - 2log likelihood ratios showed that LENT score was more, strongly associated with 6-month mortality than PROMISE (p = 0.001) or RECLS (p = 0.02). LENT score was also more strongly associated with 1-year mortality than PROMISE (p = 0.001) but there was no difference between LENT and RECLS score (p = 0.64). We observed that the LENT score was more predictive than the other scores in mortality in patients who have lung cancer and MPE. The LENT and RECLS scores have similar performance characteristics for prediction of 1-year mortality in these patients.

Integrating Multi-Organ Imaging-Derived Phenotypes and Genomic Information for Predicting the Occurrence of Common Diseases.

As medical imaging technologies advance, these tools are playing a more and more important role in assisting clinical disease diagnosis. The fusion of biomedical imaging and multi-modal information is profound, as it significantly enhances diagnostic precision and comprehensiveness. Integrating multi-organ imaging with genomic information can significantly enhance the accuracy of disease prediction because many diseases involve both environmental and genetic determinants. In the present study, we focused on the fusion of imaging-derived phenotypes (IDPs) and polygenic risk score (PRS) of diseases from different organs including the brain, heart, lung, liver, spleen, pancreas, and kidney for the prediction of the occurrence of nine common diseases, namely atrial fibrillation, heart failure (HF), hypertension, myocardial infarction, asthma, type 2 diabetes, chronic kidney disease, coronary artery disease (CAD), and chronic obstructive pulmonary disease, in the UK Biobank (UKBB) dataset. For each disease, three prediction models were developed utilizing imaging features, genomic data, and a fusion of both, respectively, and their performances were compared. The results indicated that for seven diseases, the model integrating both imaging and genomic data achieved superior predictive performance compared to models that used only imaging features or only genomic data. For instance, the Area Under Curve (AUC) of HF risk prediction was increased from 0.68 ± 0.15 to 0.79 ± 0.12, and the AUC of CAD diagnosis was increased from 0.76 ± 0.05 to 0.81 ± 0.06.

Exploring the intersection of polygenic risk scores and prenatal alcohol exposure: Unraveling the mental health equation.

BACKGROUND: Prenatal alcohol exposure poses significant risks to offspring mental health. However, the interplay between genetic predispositions to mental health disorders and prenatal alcohol exposure remains incompletely understood, limiting our ability to develop effective interventions for these conditions. METHODS: Data from the Adolescent Brain and Cognitive Development (ABCD) Study were analyzed to explore associations between polygenic risk scores (PRS) for mental disorders and maternal alcohol consumption during pregnancy. Logistic regression and structural equation modeling were utilized to assess these relationships. RESULTS: Maternal alcohol consumption after pregnancy awareness was significantly associated with an increased genetic risk for specific mental health disorders, particularly bipolar disorder in offspring. The relationship between maternal alcohol consumption and mental health outcomes was influenced by polygenic risk scores, with both externalizing and internalizing problems being affected. CONCLUSIONS: Our findings highlight the specific interaction between increased genetic risk for bipolar disorder and prenatal alcohol exposure in shaping offspring mental health outcomes. The significant associations we observed underscore the importance of considering both polygenic risk scores and prenatal alcohol exposure when assessing mental health risks in children. These insights emphasize the need for targeted interventions that address both genetic predispositions and environmental exposures to better understand and mitigate the impact on offspring mental health.

Evaluating the performance of egami, kobayashi and sano scores in predicting IVIG resistance in infant kawasaki disease.

BACKGROUND: This study aimed to evaluate the effectiveness of Egami, Kobayashi and Sano scores in predicting intravenous immunoglobulin (IVIG) resistance in infant Kawasaki disease (KD), considering its unique clinical presentation. METHODS: We retrospectively analysed 143 infants aged < 12 months and diagnosed with KD at a single centre from 2019 to 2023. Patients were divided into IVIG-resistant and IVIG-responsive groups. Demographic, clinical and laboratory data were compared between the groups. The diagnostic performance of Egami, Kobayashi and Sano scores in predicting IVIG resistance was evaluated using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the receiver operating characteristic curve (AUC). Additionally, we developed a new scoring system based on significant predictors identified in our cohort. RESULTS: Among 143 infants, 45 (31.5%) showed IVIG resistance. The IVIG-resistant group had a significantly higher rate of coronary artery lesions (15.6% vs. 5.1%, p = 0.036). Incomplete KD was observed in 61.5% of cases. Egami, Kobayashi and Sano scores exhibited low sensitivity (35.6%, 55.6% and 20%, respectively) and moderate specificity (77.6%, 63.3% and 95.9%, respectively) in predicting IVIG resistance. The AUC ranged from 0.583 to 0.674, indicating poor to fair discriminative ability. Our newly developed scoring system, based on total bilirubin and albumin levels, showed similar performance (AUC 0.633) to existing scores. CONCLUSIONS: Existing Japanese risk scoring systems and our newly developed score showed limited effectiveness in predicting IVIG resistance in infant KD. The high proportion of incomplete presentation and IVIG resistance in infants highlights the need for age-specific risk assessment and management. Further research is necessary to develop more sophisticated, dedicated prediction model for IVIG resistance in infants with KD.

Polygenic Interactions With Environmental Exposures in Blood Pressure Regulation: The HUNT Study.

BACKGROUND: The essential hypertension phenotype results from an interplay between genetic and environmental factors. The influence of lifestyle exposures such as excess adiposity, alcohol consumption, tobacco use, diet, and activity patterns on blood pressure (BP) is well established. Additionally, polygenic risk scores for BP traits are associated with clinically significant phenotypic variation. However, interactions between genetic and environmental risk factors in hypertension morbidity and mortality are poorly characterized. METHODS AND RESULTS: We used genotype and phenotype data from up to 49 234 participants from the HUNT (Trøndelag Health Study) to model gene-environment interactions between genome-wide polygenic risk scores for systolic BP and diastolic BP and 125 environmental exposures. Among the 125 environmental exposures assessed, 108 and 100 were independently associated with SBP and DBP, respectively. Of these, 12 interactions were identified for genome-wide PRSs for systolic BP and 4 for genome-wide polygenic risk scores for diastolic BP, 2 of which were overlapping (P < 2 × 10-4). We found evidence for gene-dependent influence of lifestyle factors such as cardiorespiratory fitness, dietary patterns, and tobacco exposure, as well as biomarkers such as serum cholesterol, creatinine, and alkaline phosphatase on BP. CONCLUSIONS: Individuals that are genetically susceptible to high BP may be more vulnerable to common acquired risk factors for hypertension, but these effects appear to be modifiable. The gene-dependent influence of several common acquired risk factors indicates the potential of genetic data combined with lifestyle assessments in risk stratification, and gene-environment-informed risk modeling in the prevention and management of hypertension.

Advanced Non-linear Modeling and Explainable Artificial Intelligence Techniques for Predicting 30-Day Complications in Bariatric Surgery: A Single-Center Study.

PURPOSE: Metabolic bariatric surgery (MBS) became integral to managing severe obesity. Understanding surgical risks associated with MBS is crucial. Different scores, such as the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP), aid in patient selection and outcome prediction. This study aims to evaluate machine learning (ML) models performance in predicting 30-day post-operative complications and compare them with the MBSAQIP risk score. MATERIALS AND METHODS: We retrospectively evaluated 424 consecutive patients (2006-2020) who underwent MBS, analyzing 30-day surgical complications according to Clavien-Dindo Classification. ML models, including logistic regression, support vector machine, random forest, k-nearest neighbors, multi-layer perceptron, and extreme gradient boosting, were analyzed and compared to MBSAQIP risk score. Performance was measured by area under receiver operating characteristic curve (AUROC) analysis. RESULTS: Random forest showed the highest AUROC in the training (AUROC = 0.94) and the validation set (AUROC = 0.88). ML algorithms, particularly random forest, outperformed MBSAQIP in predicting negative 30-day outcomes in both the training and validation sets (AUROC = 0.64, DeLong's Test p < 0.001). The five features that were more relevant for the prediction of the random forest model were serum alkaline phosphatase, platelet count, triglycerides, glycated hemoglobin, and albumin. CONCLUSION: We developed several ML model that identifies patients at risk for 30-day complications after MBS. Among these, random forest is the most performing one and outperforms the already established MBSAQIP score. This model could increase the identification of high-risk patients before MBS.