Genetic Score Research Articles

Poorer online cognitive performance is associated with genetic risk for Alzheimer’s disease and brain phenotypes in healthy mid‐life and older adults.

AbstractBackgroundSelf‐administered online cognitive testing offers a cost‐effective and flexible alternative to in‐person neuropsychological assessments. We used the Creyos platform (previously named Cambridge Brain Sciences) to assess cognitive function in a large sample (N = 1673) of middle aged and older adults participating in the PISA (Prospective Imaging Study of Aging) study. PISA aims to characterise the early symptoms and progression of Alzheimer’s disease at its prodromal phase.MethodWe have utilised our Australia‐wide population based sample recruitment pool of research participants with genome wide genotyping. Participants completed a comprehensive online survey and online cognitive assessments, including Creyos, consisting of 12 self‐administered tasks covering memory, executive function, language, and visuo‐spatial domains. Using genetic profile scores in a sample size of 1,673 (70% female, aged 42‐75 years, mean 60.8). We tested the association between cognitive test results and genetic risk for Alzheimer’s disease and related phenotypes including structural neuroimaging measures.ResultsOur findings indicate a significant association of Alzheimer’s polygenic risk scores (PRS) with cognitive test results in healthy individuals within memory and executive function domains. The results of analyses with additional genetic profile scores including psychiatric traits and structural neuroimaging measures will also be presented.ConclusionThose who are at high genetic risk for Alzheimer’s disease have reduced cognitive function prior to dementia diagnosis from middle age. Our results highlight the utility of online cognitive testing as a cost‐effective alternative to in person testing for large scale studies and the potential for it’s used as a pre‐screening approach to identify those at high risk of Alzheimer’s disease.

The Prediction of Alzheimer’s Disease through Multi‐Trait Genetic Modeling

AbstractBackgroundPrevious studies have indicated that prediction performance of a genetic risk score is improved when the score is built using information about multiple traits/risk factors associated with the target trait. To better capture the polygenic architecture of Alzheimer’s Disease, we developed a joint genetic score, MetaGRS.MethodWe incorporated genetic variants for AD and 24 other traits from two independent cohorts, NACC (n = 3,174, training set) and UPitt (n = 2,053, validation set).ResultOne standard deviation increase in the MetaGRS is associated with about a 57% increase in the AD risk (HR = 1.577, p = 7.17 E‐56), showing little difference from the HR for AD GRS alone (HR = 1.579, p = 1.20E‐56), suggesting similar utility of both models. We also conducted APOE stratified analyses to assess the role of the e4 allele on risk prediction. Similar to that of the combined model, our stratified results did not show a considerable improvement of the MetaGRS.ConclusionOur study showed that prediction power of the MetaGRS significantly outperformed that of the reference model without any genetic information, but was effectively equivalent to the prediction power of the AD GRS in both the full and stratified analyses. Our findings are broadly consistent with previous studies of Stroke and T2D.

Association of human brain‐age with genetically predicted plasma levels of brain rejuvenating and aging factors identified in mice

AbstractBackgroundAging is the primary risk factor for Alzheimer’s disease. Experiments in mice have identified circulating proteins with an “aging/rejuvenating” effect on the brain. However, whether these proteins have an effect on the human brain remains unknown. Here, we leverage genetic data to study links between the predicted plasma levels of these proteins and human brain age.MethodsThis study includes 1,394 cognitively unimpaired individuals of the ALFA study. Plasma proteins with an effect on mice brain aging were identified through a systematic review [Figure 1]. Summary statistics data of protein quantitative trait loci (pQTLs) associated to these proteins in human (inclusion threshold<5×10−5) were acquired from a previous study (Pietzner et al.,2021), and used for computing protein genetic scores (pPRS). For each ALFA cohort participant, DeltaAge scores was calculated by subtracting chronological age from MRI‐based estimation of brain age (Cumplido et al.,2022). Positive values are interpreted as brain age older than chronological age, and viceversa. The associations between brain DeltaAge measurements and pPRSs were assessed through general linear regression models stratified by sex, amyloid‐β (Aβ) status (CSF‐Aβ42/40<0.071 [Milà‐Alomà et al.,2020]) and APOE‐ε4 carriership. Results were reported for nominal and group‐correction (two experimental aging groups) level of significance (p<0.05, p<0.025, respectively). All pQTLs included in the significant pPRS were functionally annotated and an enrichment analysis was performed.ResultsGenetically predicted plasma levels of CSF2, VCAM1, HP, GHRH and BGLAP were associated with negative values of brain DeltaAge, while KLOTHO with positive values. Results for GHRH (Aβ+ and APOE‐ε4 non‐carriers) and BGLAP (APOE‐ε4 carriers) remained significant after p‐value correction, with an effect in agreement with their brain rejuvenation role as found in mice [Figure 2]. Enrichment analysis found immune response and complement activation processes associated with negative values of DeltaAge [Figure 3].ConclusionsThese results show that plasma levels of the brain aging/rejuvenating proteins discovered in mice may also influence human brain aging. In particular, genetically predicted levels of two rejuvenating factors in mice (BGLAP and GHRH) were associated with a younger brain age than chronological age. Follow‐up analyses will include protein level measurements to unravel the molecular complexity of brain aging.

Variation in VEGFA and risk of cardiovascular disease in the UK Biobank

BackgroundCardiovascular disease (CVD) is an escalating global health crisis, contributing significantly to worldwide mortality and morbidity. Dyslipidemia stands as a critical risk factor for CVD. Vascular endothelial growth factor A (VEGFA) is pivotal in angiogenesis and represents a clinical target for CVD intervention. However, the impact of genetic modulation of VEGFA on lipid levels and the subsequent risk of cardiovascular events remains unclear.MethodsWe used LDpred2 to calculate genetic scores for lipid levels based on VEGFA variation, serving as instrumental variables to simulate the effect of VEGFA inhibitors. We then assessed the associations between genetic risk for lipid levels and CVD risk by conducting One-sample Mendelian randomization.ResultsOur results indicated that low-density lipoprotein cholesterol [LDL-C; odds ratio (OR) = 1.09, 95% CI: 1.06–1.11], remnant cholesterol (RC; OR = 1.24, 95% CI: 1.13–1.36), and triglycerides (TG; OR = 1.14, 95% CI: 1.07–1.22) were positively associated with the incidence of CVD. In contrast, high-density lipoprotein cholesterol (HDL-C) was inversely associated with the incidence of CVD (OR = 0.80, 95% CI: 0.76–0.86). When considering the genetic score for LDL-C constructed based on VEGFA, the group with a high genetic score demonstrated an elevated CVD risk (OR = 1.11, 95% CI: 1.04–1.19) compared to those with a low genetic score. Notably, One-sample Mendelian randomization results provided evidence of a causal relationship between LDL-C and CVD (p = 8.4×10−3) when using genetic variation in VEGFA as an instrumental variable.ConclusionsGenetic variation mimicking the effect of VEGFA inhibition, which lowers LDL-C levels, was causally associated with a reduced risk of cardiovascular events. These findings offer insight into the potential therapeutic relevance of modulating VEGFA-mediated lipid changes in the prevention and management of CVD.

The value of genetic data from 665,460 individuals in managing iron deficiency anaemia and suitability to donate blood.

Although the genetic determinants of haemoglobin and ferritin have been widely studied, those of the clinically and globally relevant iron deficiency anaemia (IDA) and deferral due to hypohaemoglobinemia (Hb-deferral) are unclear. In this investigation, we aimed to quantify the value of genetic information in predicting IDA and Hb-deferral. We analysed genetic data from up to 665,460 participants of the FinnGen, Blood Service Biobank and UK Biobank, and used INTERVAL (N = 39,979) for validation. We performed genome-wide association studies (GWASs) of IDA and Hb-deferral and utilized publicly available genetic associations to compute polygenic scores for IDA, ferritin and Hb. We fitted models to estimate the effect sizes of these polygenic risk scores (PRSs) on IDA and Hb-deferral risk while accounting for the individual's age, sex, weight, height, smoking status and blood donation history. Significant variants in GWASs of IDA and Hb-deferral appear to be a small subset of variants associated with ferritin and Hb. Effect sizes of genetic predictors of IDA and Hb-deferral are similar to those of age and weight which are typically used in blood donor management. A total genetic score for Hb-deferral was estimated for each individual. The odds ratio estimate between first decile against that at ninth decile of total genetic score distribution ranged from 1.4 to 2.2. The value of genetic data in predicting IDA or suitability to donate blood appears to be on a practically useful level.

Editorial: Clinical implementation of genetic scores in cardiovascular medicine

Editorial: Clinical implementation of genetic scores in cardiovascular medicine

INNV-38. PREDICTING THE CLINICAL PHENOTYPE IN NF2 RELATED SCHWANNOMATOSIS PATIENTS

Abstract BACKGROUND Different genetic scores have been proposed to predict the phenotype of NF2 related Schwannomatosis (NF2 -SCHW MIM # 101000) , a rare autosomal dominant familial cancer syndromes caused by pathogenic variants of the NF2 gene. The UK NF2 Reference Group proposed the Genetic Severity Score (GSS) based on the type and location of NF2 germline variant observed. Catasus et al. suggested a new score based also on a functional assay of Merlin and its downstream pathways (FGSS). Recently Teranish et al. used targeted deep sequencing to predict functional prognosis in those patients. Material and METHODS 70 patients (median age 40) were identified by scanning the electronic NF2-SCHW patient database at Fondazione IRCCS C. Besta,. The median follow-up was 14 yrs. Clinical diagnosis was established following the Updated diagnostic criteria and nomenclature for neurofibromatosis type 2 and schwannomatosis”. All patients underwent NF2, SMARCB1 and LZTR1 mutational screening by NGS and MPLA analysis using blood DNA or the tissue of two different tumors when available. NF2 gene germline pathogenic were found in 45 subjects (64%), in most cases NF2 point mutations, but in 4 cases and whole gene deletions was observed and in 2 a ring NF2 chromosome was identified, in four cases a mosaic NF2-SCH was identified and in 21 (30%) patients no pathogenic variant was found. We assessed NF2 clinical phenotype in relation to the UK GSS and FGSS to validate their use. RESULTS The disease phenotype differed significantly depending both on clinical and genetic factors.. GSS and FGSS showed significant correlation with several measures, allowing stratification of patients with severe and mild disease but not with moderate phenotype. Furthermore, we provided evidence on correlation between whole NF2 deletion extent and phenotype severity. Large cohorts of NF2-SCHW patients are needed to identify more accurate scores.

EPID-33. MORTALITY AND CAUSE OF DEATH RELATED TO CLINICAL AND GENETIC SEVERITY IN PATIENTS WITH NEUROFIBROMATOSIS TYPE 2 – SCHWANNOMATOSIS

Abstract OBJECTIVES This study aimed to investigate the circumstances of death in NF2 patients, focusing on clinical and genetic severity. METHODS Data from three major German NF2 centers were analyzed retrospectively. A total of 199 patients were included, with follow-up periods ranging from 6 months to 30 years. Disease severity was assessed using clinical and genetic classification scales with three grades each. At the time of data analysis, 36 patients had died in all three centers combined. RESULTS Of the 36 deceased patients, 47.2% had moderate clinical severity, 38.9% had severe disease, 13,9% were classified as grade 1. Genetic severity could be determined for 15 patients with 66.7% categorized as a moderate NF2 and 20.0% as genetically severe NF2. Only 13.3% had tissue mosaicism associated with a mild genetic severity. Patients with moderate clinical severity died at a mean age of 44.5 years (± 20.97), patients in grade 3 died at 46.89 years (± 11.71), and grade 1 patients died at 35.1 years (± 31.36) in this cohort. Patients with the highest genetic severity score died earlier (mean age = 35.5 years ± 2.29) than those with a moderate severity (51.3 years ± 21.65). The most common causes of death were malignant neoplasms, cerebral insults, and pneumonia, each accounting for three of the cases. Other causes of death included road traffic fatalities, septic shock, cerebral compression, and suicide, with 16.6% of cases involving attempted suicide. CONCLUSIONS The study emphasizes the need for a wider registry to assess prognosis, to stratify major risk factors causing mortality in NF2 and to verify correlations to clinical and genetic severity scales. Increased suicide and attempted suicide rates among NF2 patients highlight the importance of psychological counseling in patient management.

Abstract 17570: Combining Genomic Profiling and Clinical Data Through Machine Learning Modeling for the Prediction of Coronary Artery Disease Severity: Insights From the Genetic SYNTAX Score (GESS) Trial

Background: Genomic profiling emerges as a powerful partner in the prediction of CAD development. Hypothesis: Machine learning (ML) algorithms integrating genomic profiling and clinical data could improve patient outcomes by contributing to earlier non-invasive diagnosis of obstructive CAD. Aims: The Genetic Syntax Score (GESS) prospective cohort study aimed to create a ML-algorithm able to predict the severity of CAD based on the analysis of 228 single nucleotide polymorphisms (SNPs) and relevant clinical and demographic data. Ultimate goal of this analysis was to compare the predictive capacity of a SNP-including model with that of a clinical model without SNPs. Methods: Patients with suspected CAD (n=919, mean age: 64±12 years) underwent invasive coronary angiography (from 2019 to 2021), and, thereby, their SYNTAX score was determined. Peripheral blood samples were drawn for genomic profiling (next generation sequencing analysis of a custom-made panel consisting of 228 SNPs) under standardized methods. After the ML-based selection of the most important subset of features (clinical/SNPs), two competing meta-learners were fitted, called Model A (including clinical/demographic predictors) and Model B (Model A plus SNPs predictors). The difference in their predictive capacities for the precise assessment of CAD risk (whether a patient presents with SYNTAX score >0 or =0) and CAD severity (whether a patient presents with higher SYNTAX score) was investigated via Delong’s test and Wilcoxon signed-rank test, respectively. Results: Our ML-algorithm identified a total of 8 SNPs (rs11984041, rs41291556, rs2023938, rs2107595, rs216172, rs1800562, rs3732379, and rs964184) as significant predictors of CAD risk, and 7 SNPs (rs4845625, rs6689306, rs2046934, rs1332844, rs6801273, rs663129, and rs870142) as significant predictors of CAD severity. Model B demonstrated superior performance compared to Model A (Z=2.451, p=0.014 for CAD risk assessment, and V=16731, p=0.002 for CAD severity assessment). Conclusion(s): The combined use of clinical/demographic parameters and genomic profiling might be deployed to improve the prediction of CAD risk and severity under the guidance of ML-techniques. Registration: NCT03150680

Use of comprehensive genomic profiling for biomarker discovery for the management of non-small cell lung cancer brain metastases.

Clinical biomarkers for brain metastases remain elusive. Increased availability of genomic profiling has brought discovery of these biomarkers to the forefront of research interests. In this single institution retrospective series, 130 patients presenting with brain metastasis secondary to Non-Small Cell Lung Cancer (NSCLC) underwent comprehensive genomic profiling conducted using next generation circulating tumor deoxyribonucleic acid (DNA) (Guardant Health, Redwood City, CA). A total of 77 genetic mutation identified and correlated with nine clinical outcomes using appropriate statistical tests (general linear models, Mantel-Haenzel Chi Square test, and Cox proportional hazard regression models). For each outcome, a genetic signature composite score was created by summing the total genes wherein genes predictive of a clinically unfavorable outcome assigned a positive score, and genes with favorable clinical outcome assigned negative score. Seventy-two genes appeared in at least one gene signature including: 14 genes had only unfavorable associations, 36 genes had only favorable associations, and 22 genes had mixed effects. Statistically significant associated signatures were found for the clinical endpoints of brain metastasis velocity, time to distant brain failure, lowest radiosurgery dose, extent of extracranial metastatic disease, concurrent diagnosis of brain metastasis and NSCLC, number of brain metastases at diagnosis as well as distant brain failure. Some genes were solely associated with multiple favorable or unfavorable outcomes. Genetic signatures were derived that showed strong associations with different clinical outcomes in NSCLC brain metastases patients. While these data remain to be validated, they may have prognostic and/or therapeutic impact in the future. Using Liquid biopsy in NSCLC brain metastases patients, the genetic signatures identified in this series are associated with multiple clinical outcomes particularly these ones that lead to early or more numerous metastases. These findings can be reverse-translated in laboratory studies to determine if they are part of the genetic pathway leading to brain metastasis formation.

Higher atherogenic risk in schoolchildren is associated with MTMR9 rs2293855 gene polymorphism and genetic score.

Childhood dyslipidaemia is associated with the occurrence of cardiovascular diseases in adulthood, so evaluating whether an individual has a genetic predisposition to this pathology is of great importance for early action of prevention and treatment. This study aimed to evaluate the association between the FTO (rs9939609), MC4R (rs17782313) and MTMR9 (rs2293855) polymorphisms, the obesity-related genetic risk score and atherogenic risk in Brazilian children. This is a cross-sectional study conducted in 544 children aged 4-9 years in the city of Viçosa, Minas Gerais state, Brazil. The single nucleotide polymorphisms rs9939609, rs17782313 and rs2293855, were identified by the system TaqMan SNP genotyping and the obesity-related genetic risk score was determined. The lipid profile (serum total cholesterol [TC], high density lipoprotein [HDL] cholesterol, low density lipoprotein [LDL] cholesterol, triglycerides) was analysed and the atherogenic indices (Castelli I and II indices), atherogenic coefficient (AC), lipoprotein combined index (LCI) and plasma atherogenic index (PAI) were calculated. A semi-structured questionnaire was applied, obtaining data on the sociodemographic, economic and lifestyle characteristics of the children. Weight and height measurements were performed in all children, and body composition was evaluated by Dual-Energy X-ray Absorptiometry (DXA). 55.5% of the sample had dyslipidaemia, while 28.5% of the sample had at least one polymorphism and 2.2% had three polymorphisms. Children with the AG/AA genotypes in the rs2293855 polymorphism had lower HDL cholesterol levels and higher TC/HDL cholesterol, LDL/HDL cholesterol ratios and AC. Those with one or more polymorphisms (rs9939609, rs17782313 and rs2293855) in the genetic risk score had lower HDL cholesterol levels and higher TC/HDL cholesterol ratios, AC, LCI and PAI. In conclusion, the risk allele of the rs2293855 polymorphism and a higher obesity-related genetic risk score were positively associated with higher atherogenic risk in Brazilian children.

What is the Cow-Calf Economics of Genetic Panel Scores for Feedlot Traits?

AbstractPast research has only studied genetic panel scores and feedlot performance. This research combines impacts of genetic panel scores on a cow-calf operation with previously estimated feedlot impacts to evaluate the potential for misaligned economic incentives in the beef industry. Calves that were higher genetic scores for two carcass traits, marbling and tenderness, had lower weaning weights and lower net returns. Correlations between genetic traits and cow size were small and mostly insignificant. The sum of the effects on feedlot and cow-calf sectors of a one-unit higher panel score totaled $-2.83 per cow year for marbling and $-4.93 per cow year for tenderness.

Consistent effects of the genetics of happiness across the lifespan and ancestries in multiple cohorts

Happiness is a fundamental human affective trait, but its biological basis is not well understood. Using a novel approach, we construct LDpred-inf polygenic scores of a general happiness measure in 2 cohorts: the Adolescent Brain Cognitive Development (ABCD) cohort (N = 15,924, age range 9.23–11.8 years), the Add Health cohort (N = 9129, age range 24.5–34.7) to determine associations with several well-being and happiness measures. Additionally, we investigated associations between genetic scores for happiness and brain structure in ABCD (N = 9626, age range (8.9–11) and UK Biobank (N = 16,957, age range 45–83). We detected significant (p.FDR < 0.05) associations between higher genetic scores vs. several well-being measures (best r2 = 0.019) in children of multiple ancestries in ABCD and small yet significant correlations with a happiness measure in European participants in Add Health (r2 = 0.004). Additionally, we show significant associations between lower genetic scores for happiness with smaller structural brain phenotypes in a white British subsample of UK Biobank and a white sub-sample group of ABCD. We demonstrate that the genetic basis for general happiness level appears to have a consistent effect on happiness and wellbeing measures throughout the lifespan, across multiple ancestral backgrounds, and multiple brain structures.

Genetic diversity and molecular analysis using RAPD markers of banana cultivars in the five regions of East Java, Indonesia

Abstract. Slameto. 2023. Genetic diversity and molecular analysis using RAPD markers of banana cultivars in the five regions of East Java, Indonesia. Biodiversitas 24: 5035-5043. The study explored banana plants in East Java, Indonesia, specifically in the districts of Jember, Banyuwangi, Bondowoso, Situbondo, and Lumajang, using Random Amplified Polymorphic Deoxyribonucleic Acid (RAPD) markers. Thirty accessions of Musa ssp. were collected from these five districts, revealing a high level of genetic diversity. Primers OPA-04 and OPC-05 were suitable for assessing genetic variation in banana plants. It was found that the OPD-07 primer produced the fewest DNA bands (8 bands and 7 polymorphic bands), while the OPA-04 primer produced the maximum number of DNA bands (14 bands, with 9 polymorphic bands). The OPB-08 primer had the lowest polymorphism percentage (56%), and the OPC-05 primer had the greatest percentage (92%). With genetic similarity scores ranging from 0.04 (Bigih Tanjung Glugur and Lilin Banyuwangi) to 0.94 (Agung Banyuwangi and Let). The phylogenetic tree of 30 banana plants formed two primary clusters: cluster I and II, included 26 and 4 banana varieties respectively. In addition, molecular variance (AMOVA) resulted a significant proportion (93%) of genetic diversity within the population. Further studies using more precise genetic markers are still needed to determine the exact identity of the banana plant genome.

SAT308 An Assessment Of Prognostic Markers To Predict Metastatic Pheochromocytoma/Paraganglioma

Abstract Disclosure: M.D. Lundholm: None. E. Berber: None. P.P. Rao: None. Introduction: Pheochromocytoma/paraganglioma (PCC/PGL, or PPGL) are rare neuroendocrine tumors arising from chromaffin cells. Early identification of PPGL with metastatic potential is a diagnostic challenge. More data are needed on features and scoring markers used to predict PPGL metastasis. Methods: A single-center, retrospective observational study was performed of consecutive patients with pathology-confirmed PPGL from 2005 to 2022. Features associated with metastasis were identified and Pheochromocytoma of the Adrenal gland Scaled Score (PASS), Age, Size, Extra-adrenal location and Secretory type (ASES) score, and Size, Genetic, Age, and PASS (SGAP) score were calculated. Results: We identified 371 patients with PPGL (251 PCC, 120 PGL), age 52.2±15.4yrs, 60.6% female, 69.8% incidental. Metastatic disease was reported in 13.2% (N=49; 30 PCC, 19 PGL) associated with younger age (47.3 vs 53.0yrs, p=0.029), larger tumor size (6.3 vs 4.0cm, p&amp;lt;0.001), histologic findings of necrosis (26% vs 2.5%, p&amp;lt;0.001) and vascular invasion (42.1% vs 19.6% p=0.038), hyperadrenergic symptoms at diagnosis (38.8% vs 22.0%, p=0.038), norepinephrine-only secreting tumors (59.6% vs 30.1%, p&amp;lt;0.001), extra-adrenal location (51.0% vs 32.0%, p=0.009), presence of genetic mutations (72.4% vs 38.5%, p&amp;lt;0.001), particularly SDHx (31.0% vs 12.2%, p=0.020) and VHL mutations (24.1% vs 3.8%, p=0.001). There were no significant differences by gender, race, other histologic criteria from PASS, or other mutations such as RET or NF-1. ASES was positive (≥2) in 27.2% (N=100/371) with sensitivity (SN) 79.6%, specificity (SP) 81.1%, positive predictive value (PPV) 39.0%, and negative predictive value (NPV) 96.3% for predicting metastatic disease. PASS and SGAP could only be applied to patients with PCC: PASS was positive (≥4) in 29.7% (N=55/185) with SN 60.0%, SP 73.9%, PPV 21.8%, and NPV 93.8%. SGAP was positive (≥5) in 27.6% (N=32/116) with SN 56.3%, SP 77.0%, PPV 28.1%, and NPV 91.7%. Discussion: Metastatic PPGL is associated with age, tumor size and location, select histologic findings, symptomatic presentation, hormone-secreting pattern, and select genetic mutations. PPGL scoring markers ASES, PASS, and SGAP were all effective at identifying cases with low likelihood of metastasis, but had poor PPV. ASES outperformed PASS and SGAP in test metrics and practicality as the only clinically-derived marker which could be applied to all cases of PPGL. ASES can also be used pre-operatively. Most histologic features and genetic mutations included in PASS and SGAP were not strongly correlated with metastasis, though limited by lower prevalence in the study population. Conclusion: Our data supports the use of ASES alongside data on necrosis, vascular invasion, SDHx and VHL mutations where available to fine-tune our prediction of metastatic potential for PPGL. Presentation: Saturday, June 17, 2023

Dopamine multilocus genetic profile influence on reward network in chronic insomnia disorder with depression

BackgroundChronic insomnia disorder (CID) is frequently comorbid with depression, and both conditions are believed to involve disruptions in the reward network. However, the potential effects of genetic polymorphisms in modulating this network remain largely unexplored. MethodsIn this study, we recruited 50 CID patients with high (CID-HD) and low (CID-LD) depressive symptoms and assessed their reward networks using resting-state functional MRI. Additionally, we calculated the multilocus genetic profile score (MGPS) to examine the influence of depression and dopamine genetic variation on the nucleus accumbens functional connectivity (NAFC) network in CID patients. ResultsAlthough the MGPS did not show a significant difference between the two CID groups, its influence on the NAFC network was observed in the salience network (SN) and visual network (VN) in CID patients. When comparing CID-HD patients to CID-LD patients, we found that CID-HD patients exhibited decreased NAFC in the internal reward network, default mode network, SN, and sensorimotor network, while showing increased NAFC in the executive control network (ECN) and VN. Furthermore, the influence of MGPS on the reward network was only significant in CID-HD patients, specifically in the internal reward network and ECN. ConclusionThese findings suggest that genetic variations related to dopamine may modulate the reward network differently in CID patients with and without depressive symptoms. These results contribute to our understanding of the pathophysiology of polygenic effects underlying brain network abnormalities in CID patients with depression.

Overall Obesity Not Abdominal Obesity Has a Causal Relationship with Obstructive Sleep Apnea in Individual Level Data.

Both obstructive sleep apnea (OSA) and obesity are highly prevalent worldwide, and are intrinsically linked. Previous studies showed that obesity is one of the major risk factors for OSA, but the causality of the relationship is still unclear. The study was to investigate the causal relationships of overall obesity and abdominal obesity with OSA and its quantitative traits. In this case-control study, a total of 7134 participants, including 4335 moderate-to-severe OSA diagnosed by standard polysomnography and 2799 community-based controls were enrolled. Anthropometric and biochemical data were collected. Mendelian randomization (MR) analyses were performed using the genetic risk score, based on 29 body mass index (BMI)- and 11 waist-hip-ratio (WHR)-associated single nucleotide polymorphisms as instrumental variables. The causal associations of these genetic scores with OSA and its quantitative phenotypes were analyzed. Obesity was strongly correlated with OSA in observational analysis (β= 0.055, P = 3.7 × 10-5). In MR analysis, each increase by one standard deviation in BMI was associated with increased OSA risk [odds ratio (OR): 2.21, 95% confidence interval (CI): 1.62-3.02, P = 5.57 × 10-7] and with 2.72-, 4.68-, and 3.25-fold increases in AHI, ODI, and MAI, respectively (all P < 0.05) in men. However, no causal associations were found between WHR and OSA risk or OSA quantitative traits in men and women. Compared to abdominal obesity, overall obesity showed a causal relationship with OSA and its quantitative traits, especially in men.

IGF1 Genetic Polymorphism and the Association between Vitamin D Status and BMI Percentiles in Children.

Both the IGF1 axis and hypovitaminosis D play a role in childhood obesity, either as a cause or a causality. While some studies suggest an interrelation between vitamin D status, IGF1, and obesity, this mechanism remains obscure. The aim of this study, therefore, was to explore associations between four genetic polymorphisms in the IGF1 axis in hypovitaminosis D-related obesity. The study included 116 pre-pubertal Israeli Arab children (52 girls), mean age 9.4 ± 2.6. Serum 25(OH)D was measured and anthropometric measures were obtained. Genomic DNA was extracted from peripheral EDTA-treated anti-coagulated blood using a standard protocol. Genotypes were determined using the Taqman allelic discrimination assay. The IGF genetic score was computed according to the additive genetic score model. A moderate-to-high negative correlation (r = 0.580, p < 0.05) was seen between the vitamin D status and body mass index (BMI) percentile of participants with high GS. Yet, no correlations were seen between vitamin D status and BMI percentile for participants with a low-to-moderate genetic score (GS) (GS ≤ 2). These results suggest that IGF1 genetic scores associated with elevated circulating IGF1 may indicate a tendency toward developing hypovitaminosis D-associated obesity.

20 Developmental Outcomes of a Cohort of Preschool Children Requiring Craniosynostosis Surgery in Manitoba

Abstract Background Historically in Manitoba, all children with craniosynostosis were referred to the Child Development Clinic (CDC) for neurodevelopmental evaluation, because craniosynostosis has been associated with developmental delay. However, due to heightened volume pressures, the CDC recently decided to limit the number of referrals accepted for evaluation of children with craniosynostosis. Objectives To inform best practices for neurodevelopmental screening, this study aims to describe the developmental outcomes of preschool children requiring craniosynostosis surgery in Manitoba. Design/Methods In this historical chart review of the CDC electronic medical record, the developmental outcomes of patients who were assessed at CDC for surgically managed craniosynostosis between July 1st, 2016 and December 1st, 2021 were described. Developmental quotients across Motor, Cognitive and Language domains were collected, and patients were categorized as Normal, Mild Delay in 1 Area or Delay in ≥2 Areas. Demographic and medical characteristics were collected, and descriptive statistics were used to describe and compare outcomes between groups. Results Out of a total of 67 children, 18% (n=12) demonstrated developmental delays in ≥2 areas, 23.9% (n=16) demonstrated mild developmental delays in one area, and 58.2% (n=39) were developmentally appropriate across all areas. Presence of genetic syndrome (p&amp;lt;0.001), suture type (p=0.011), and parental SES score (p=0.028) were significantly associated with developmental delay in ≥2 areas. Odds ratios for genetic syndrome and SES score were 218.352 (95% CI 6.843, 6967.766) and 0.857 (95% CI 0.766, 0.959) respectively. 11.9% (n=8) of children were referred to Children’s Disability Services, 5 of whom had syndrome involvement. Conclusion To target children at highest risk for developmental delay, we suggest that children with craniosynostosis be referred for neurodevelopmental evaluation if they have multisutural craniosynostosis, suspicion or confirmed genetic syndrome, or an identified developmental concern by primary care physician screening.

P20.03.A PREDICTING THE CLINICAL PHENOTYPE INNF2 RELATED SCHWANNOMATOSIS PATIENTS USING NEW GENETIC SCORES

Abstract BACKGROUND NF2 related Schwannomatosis (NF2 -SCHW MIM # 101000) is a rare autosomal dominant familial cancer syndromes caused by mutations in the NF2 gene, mainly due to NF2 point mutations or intragenic deletions. NF2 patients. In 95% of patients, bilateral vestibular schwannomas are present, but NF2 -SCHW patients can develop other tumors and show ophthalmic and dermatological signs. Several studies established a genotype-phenotype correlations; the UK NF2 Reference Group proposed a Genetic Severity Score (GSS) based on the type and location of NF2 germline variant observed. Catasus et al. after validation of the score in a Spanish cohort suggested a new score based also on a functional assay of Merlin and its downstream pathways (FGSS). Recently Teranish et al. used targeted deep sequencing to predict functional prognosis in those patients. MATERIAL AND methods 70 patients (median age 40) were identified by scanning the electronic NF2-SCHW patient database at Fondazione IRCCS C. Besta, where the patients had undergone full neurological, ophthalmic, and audiological assessment. The median follow-up was 14 yrs. Clinical diagnosis was established following the Updated diagnostic criteria and nomenclature for neurofibromatosis type 2 and schwannomatosis”. All patients underwent NF2, SMARCB1 and LZTR1 mutational screening by NGS and MPLA analysis using blood DNA or the tissue of two different tumors when available.NF2 gene germline pathogenic were found in 45 subjects (64%), in most cases NF2 point mutations, but in 4 cases and whole gene deletions was observed and in 2 a ring NF2 chromosome was identified, in four cases a mosaic NF2-SCH was identified and in 21 (30%) patients no pathogenic variant was found. We assessed NF2-SCHW clinical phenotype in relation to the UK GSS and FGSS to validate their use as clinical and research tools, despite the significant phenotypic variability observed. RESULTS The disease outcome differed significantly depending both on clinicaland genetic factors. Among these factors,” Age of symptom onset” “Truncating”, “Mosaic”, and “whole gene deletion” had the most significant effects on functional disability. Conclusion GSS and FGSS showed significant correlation with several measures, allowing stratification of patients with severe and mild disease but not with moderate phenotype. Furthermore, we provided evidence on correlation between whole NF2 deletion extent and phenotype severity. Large cohorts of NF2-SCHW patients are needed to identify more accurate scores, becoming useful tools for patient management.