Genetic modifiers of cognitive decline in PSEN1 E280A Alzheimer's disease.

INTRODUCTION: Rate of cognitive decline (RCD) in Alzheimer's disease (AD) determines the degree of impairment for patients and of burden for caretakers. We studied the association of RCD with genetic variants in AD. METHODS: RCD was evaluated in 62 familial AD (FAD) and 53 sporadic AD (SAD) cases, and analyzed by whole-exome sequencing for association with common exonic functional variants. Findings were validated in post mortem brain tissue. RESULTS: One hundred seventy-two gene variants in FAD, and 227 gene variants in SAD associated with RCD. In FAD, performance decline of the immediate recall of the Rey-Osterrieth figure test associated with 122 genetic variants. Olfactory receptor OR51B6 showed the highest number of associated variants. Its expression was detected in temporal cortex neurons. DISCUSSION: Impaired olfactory function has been associated with cognitive impairment in AD. Genetic variants in these or other genes could help to identify risk of faster memory decline in FAD and SAD patients.

Long Non-Coding RNAs and Alzheimer's Disease: Towards Personalized Diagnosis.

Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive cognitive decline, is the most common form of dementia. Currently, there is no single test that can diagnose AD, especially in understudied populations and developing countries. Instead, diagnosis is based on a combination of medical history, physical examination, cognitive testing, and brain imaging. Exosomes are extracellular nanovesicles, primarily composed of RNA, that participate in physiological processes related to AD pathogenesis such as cell proliferation, immune response, and neuronal and cardiovascular function. However, the identification and understanding of the potential role of long non-coding RNAs (lncRNAs) in AD diagnosis remain largely unexplored. Here, we clinically, cognitively, and genetically characterized a sample of 15 individuals diagnosed with AD (cases) and 15 controls from Barranquilla, Colombia. Advanced bioinformatics, analytics and Machine Learning (ML) techniques were used to identify lncRNAs differentially expressed between cases and controls. The expression of 28,909 lncRNAs was quantified. Of these, 18 were found to be differentially expressed and harbored in pivotal genes related to AD. Two lncRNAs, ENST00000608936 and ENST00000433747, show promise as diagnostic markers for AD, with ML models achieving > 95% sensitivity, specificity, and accuracy in both the training and testing datasets. These findings suggest that the expression profiles of lncRNAs could significantly contribute to advancing personalized AD diagnosis in this community, offering promising avenues for early detection and follow-up.

Uncovering the Genetic and Molecular Features of Huntington's Disease in Northern Colombia.

Huntington's disease (HD) is a genetic disorder caused by a CAG trinucleotide expansion in the huntingtin (HTT) gene. Juan de Acosta, Atlántico, a city located on the Caribbean coast of Colombia, is home to the world's second-largest HD pedigree. Here, we include 291 descendants of this pedigree with at least one family member with HD. Blood samples were collected, and genomic DNA was extracted. We quantified the HTT CAG expansion using an amplicon sequencing protocol. The genetic heterogeneity was measured as the ratio of the mosaicism allele's read peak and the slippage ratio of the allele's read peak from our sequence data. The statistical and bioinformatic analyses were performed with a significance threshold of p < 0.05. We found that the average HTT CAG repeat length in all participants was 21.91 (SD = 8.92). Of the 291 participants, 33 (11.3%, 18 females) had a positive molecular diagnosis for HD. Most affected individuals were adults, and the most common primary and secondary alleles were 17/7 (CAG/CCG) and 17/10 (CAG/CCG), respectively. The mosaicism increased with age in the participants with HD, while the slippage analyses revealed differences by the HD allele type only for the secondary allele. The slippage tended to increase with the HTT CAG repeat length in the participants with HD, but the increase was not statistically significant. This study analyzed the genetic and molecular features of 291 participants, including 33 with HD. We found that the mosaicism increased with age in the participants with HD, particularly for the secondary allele. The most common haplotype was 17/7_17/10. The slippage for the secondary allele varied by the HD allele type, but there was no significant difference in the slippage by sex. Our findings offer valuable insights into HD and could have implications for future research and clinical management.

A multifactorial model of pathology for age of onset heterogeneity in familial Alzheimer's disease.

Presenilin-1 (PSEN1) mutations cause familial Alzheimer's disease (FAD) characterized by early age of onset (AoO). Examination of a large kindred harboring the PSEN1-E280A mutation reveals a range of AoO spanning 30 years. The pathophysiological drivers and clinical impact of AoO variation in this population are unknown. We examined brains of 23 patients focusing on generation and deposition of beta-amyloid (Aß) and Tau pathology profile. In 14 patients distributed at the extremes of AoO, we performed whole-exome capture to identify genotype-phenotype correlations. We also studied kinome activity, proteasome activity, and protein polyubiquitination in brain tissue, associating it with Tau phosphorylation profiles. PSEN1-E280A patients showed a bimodal distribution for AoO. Besides AoO, there were no clinical differences between analyzed groups. Despite the effect of mutant PSEN1 on production of Aß, there were no relevant differences between groups in generation and deposition of Aß. However, differences were found in hyperphosphorylated Tau (pTau) pathology, where early onset patients showed severe pathology with diffuse aggregation pattern associated with increased activation of stress kinases. In contrast, late-onset patients showed lesser pTau pathology and a distinctive kinase activity. Furthermore, we identified new protective genetic variants affecting ubiquitin-proteasome function in early onset patients, resulting in higher ubiquitin-dependent degradation of differentially phosphorylated Tau. In PSEN1-E280A carriers, altered γ-secretase activity and resulting Aß accumulation are prerequisites for early AoO. However, Tau hyperphosphorylation pattern, and its degradation by the proteasome, drastically influences disease onset in individuals with otherwise similar Aß pathology, hinting toward a multifactorial model of disease for FAD. In sporadic AD (SAD), a wide range of heterogeneity, also influenced by Tau pathology, has been identified. Thus, Tau-induced heterogeneity is a common feature in both AD variants, suggesting that a multi-target therapeutic approach should be used to treat AD.

Executive Function and Theory of Mind in Children with ADHD: a Systematic Review.

In developmental research, the relationship between Executive Function (EF) and Theory of Mind (ToM) has been extensively assessed, and EF has been considered a condition for ToM. However, few researchers have studied the relationship between EF and ToM in clinical populations, especially that of Attention Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder characterized by symptoms of inattention and motor hyperactivity/impulsivity, in which EF is largely impaired. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model, 201 English and Spanish articles evaluating EF and ToM in ADHD were chosen. Fifteen papers met the inclusion criteria and were selected for further analysis. The first study dates from 2001. Most of the studies' designs are cross-sectional, include mostly male children, have a small sample size, and were conducted in European countries. Unlike tasks assessing EF, tasks assessing ToM were heterogeneous across studies. The EFs most correlated with ToM were inhibitory control, working memory, cognitive flexibility, and attention. Interest in studying the relationship between EF and ToM in ADHD is recent,but increasing based on new findings and tuning of ToM instruments. However, while an association between EF and ToM is indicated in ADHD, the degree of prediction and predictability of one over the other cannot yet be established because of the studies' heterogeneity.

Neuropsychological performance in patients with asymptomatic HIV-1 infection.

Human immunodeficiency virus (HIV-1) infection and acquired immunodeficiency syndrome (AIDS) lead to neurocognitive disorders; however, there is still much knowledge to be gained regarding HIV-associated neurocognitive disorders. The purpose of this study was to assess the cognitive performance, instrumental activities of daily living, depression, and anxiety in patients with asymptomatic HIV-1 infections compared with seronegative participants without neurocognitive impairment. We studied a sample consisted of 60 patients with asymptomatic HIV-1 infections and 60 seronegative participants without neurocognitive impairment from the city of Barranquilla, Colombia, with a mean age of 36.07 years. A protocol of neuropsychological and psychopathological tests was applied to the participants. The group of patients with asymptomatic HIV infections significantly underperformed on tasks that assessed global cognitive screening, attention span, learning, phonemic verbal fluency, auditory-verbal comprehension, information processing speed, cognitive flexibility, and motor skills compared to the group of seronegative participants. No significant differences were found in memory, visual confrontation naming, vocabulary, inhibition, and instrumental activities of daily living. Additionally, the patients with asymptomatic HIV-1 infection had a higher anxiety index than the seronegative participants, but no significant difference was found in depression. A correlation was found between depression and anxiety. In conclusion, the patients with asymptomatic HIV-1 infection had lower cognitive performances than the seronegative participants in the cognitive functions mentioned above and more anxiety but still performed the instrumental activities of daily living.

Definition of mutations in polyautoimmunity.

OBJECTIVES: Familial autoimmunity and polyautoimmunity represent extreme phenotypes ideal for identifying major genomic variants contributing to autoimmunity. Whole exome sequencing (WES) and linkage analysis are well suited for this purpose due to its strong resolution upon familial segregation patterns of functional protein coding and splice variants. The primary objective of this study was to identify potentially autoimmune causative variants using WES data from extreme pedigrees segregating polyautoimmunity phenotypes. METHODS: DNA of 47 individuals across 10 extreme pedigrees, ascertained from probands affected with polyautoimmunity and familial autoimmunity, were selected for WES. Variant calls were obtained through Genome Analysis Toolkit. Filtration and prioritization framework to identify mutation(s) were applied, and later implemented for genetic linkage analysis. Sanger sequencing corroborated variants with significant linkage. RESULTS: Novel and mostly rare variants harbored in SRA1, MLL4, ABCB8, DHX34 and PLAUR showed significant linkage (LOD scores are >3.0). The strongest signal was in SRA1, with a LOD score of 5.48. Network analyses indicated that SRA1, PLAUR and ABCB8 contribute to regulation of apoptotic processes. CONCLUSIONS: Novel and rare variants in genetic linkage with polyautoimmunity were identified throughout WES. Genes harboring these variants might be major players of autoimmunity.

A Mutation in DAOA Modifies the Age of Onset in PSEN1 E280A Alzheimer's Disease.

We previously reported age of onset (AOO) modifier genes in the world's largest pedigree segregating early-onset Alzheimer's disease (AD), caused by the p.Glu280Ala (E280A) mutation in the PSEN1 gene. Here we report the results of a targeted analysis of functional exonic variants in those AOO modifier genes in sixty individuals with PSEN1 E280A AD who were whole-exome genotyped for ~250,000 variants. Standard quality control, filtering, and annotation for functional variants were applied, and common functional variants located in those previously reported as AOO modifier loci were selected. Multiloci linear mixed-effects models were used to test the association between these variants and AOO. An exonic missense mutation in the G72 (DAOA) gene (rs2391191, P = 1.94 × 10(-4), P FDR = 9.34 × 10(-3)) was found to modify AOO in PSEN1 E280A AD. Nominal associations of missense mutations in the CLUAP1 (rs9790, P = 7.63 × 10(-3), P FDR = 0.1832) and EXOC2 (rs17136239, P = 0.0325, P FDR = 0.391) genes were also found. Previous studies have linked polymorphisms in the DAOA gene with the occurrence of neuropsychiatric symptoms such as depression, apathy, aggression, delusions, hallucinations, and psychosis in AD. Our findings strongly suggest that this new conspicuous functional AOO modifier within the G72 (DAOA) gene could be pivotal for understanding the genetic basis of AD.

Mutations modifying sporadic Alzheimer's disease age of onset.

The identification of mutations modifying the age of onset (AOO) in Alzheimer's disease (AD) is crucial for understanding the natural history of AD and, therefore, for early interventions. Patients with sporadic AD (sAD) from a genetic isolate in the extremes of the AOO distribution were whole-exome genotyped. Single- and multi-locus linear mixed-effects models were used to identify functional variants modifying AOO. A posteriori enrichment and bioinformatic analyses were applied to evaluate the non-random clustering of the associate variants to physiopathological pathways involved in AD. We identified more than 20 pathogenic, genome-wide statistically significant mutations of major modifier effect on the AOO. These variants are harbored in genes implicated in neuron apoptosis, neurogenesis, inflammatory processes linked to AD, oligodendrocyte differentiation, and memory processes. This set of new genes harboring these mutations could be of importance for prediction, follow-up and eventually as therapeutical targets of AD. © 2016 Wiley Periodicals, Inc.

Novel and rare functional genomic variants in multiple autoimmune syndrome and Sjögren's syndrome.

BACKGROUND: Multiple autoimmune syndrome (MAS), an extreme phenotype of autoimmune disorders, is a very well suited trait to tackle genomic variants of these conditions. Whole exome sequencing (WES) is a widely used strategy for detection of protein coding and splicing variants associated with inherited diseases. METHODS: The DNA of eight patients affected by MAS [all of whom presenting with Sjögren's syndrome (SS)], four patients affected by SS alone and 38 unaffected individuals, were subject to WES. Filters to identify novel and rare functional (pathogenic-deleterious) homozygous and/or compound heterozygous variants in these patients and controls were applied. Bioinformatics tools such as the Human gene connectome as well as pathway and network analysis were applied to test overrepresentation of genes harbouring these variants in critical pathways and networks involved in autoimmunity. RESULTS: Eleven novel and rare functional variants were identified in cases but not in controls, harboured in: MACF1, KIAA0754, DUSP12, ICA1, CELA1, LRP1/STAT6, GRIN3B, ANKLE1, TMEM161A, and FKRP. These were subsequently subject to network analysis and their functional relatedness to genes already associated with autoimmunity was evaluated. Notably, the LRP1/STAT6 novel mutation was homozygous in one MAS affected patient and heterozygous in another. LRP1/STAT6 disclosed the strongest plausibility for autoimmunity. LRP1/STAT6 are involved in extracellular and intracellular anti-inflammatory pathways that play key roles in maintaining the homeostasis of the immune system. Further; networks, pathways, and interaction analyses showed that LRP1 is functionally related to the HLA-B and IL10 genes and it has a substantial impact within immunological pathways and/or reaction to bacterial and other foreign proteins (phagocytosis, regulation of phospholipase A2 activity, negative regulation of apoptosis and response to lipopolysaccharides). Further, ICA1 and STAT6 were also closely related to AIRE and IRF5, two very well known autoimmunity genes. CONCLUSIONS: Novel and rare exonic mutations that may account for autoimmunity were identified. Among those, the LRP1/STAT6 novel mutation has the strongest case for being categorised as potentially causative of MAS given the presence of intriguing patterns of functional interaction with other major genes shaping autoimmunity.

A distance-based kernel for classification via Support Vector Machines.

Support Vector Machines (SVMs) are a type of supervised machine learning algorithm widely used for classification tasks. In contrast to traditional methods that split the data into separate training and testing sets, here we propose an innovative approach where subsets of the original data are randomly selected to train the model multiple times. This iterative training process aims to identify a representative data subset, leading to improved inferences about the population. Additionally, we introduce a novel distance-based kernel specifically designed for binary-type features based on a similarity matrix that efficiently handles both binary and multi-class classification problems. Computational experiments on publicly available datasets of varying sizes demonstrate that our proposed method significantly outperforms existing approaches in terms of classification accuracy. Furthermore, the distance-based kernel achieves superior performance compared to other well-known kernels from the literature and those used in previous studies on the same datasets. These findings validate the effectiveness of our proposed classification method and distance-based kernel for SVMs. By leveraging random subset selection and a unique kernel design, we achieve notable improvements in classification accuracy. These results have significant implications for diverse classification problems in Machine Learning and data analysis.

Theory of Mind in Huntington's Disease: A Systematic Review of 20 Years of Research.

Background: People with Huntington's disease (HD) exhibit neurocognitive alterations throughout the disease, including deficits in social cognitive processes such as Theory of Mind (ToM). Objective: The aim is to identify methodologies and ToM instruments employed in HD, alongside relevant findings, within the scientific literature of the past two decades. Methods: We conducted a comprehensive search for relevant papers in the SCOPUS, PubMed, APA-PsyArticles, Web of Science, Redalyc, and SciELO databases. In the selection process, we specifically focused on studies that included individuals with a confirmed genetic status of HD and investigated ToM functioning in patients with and without motor symptoms. The systematic review followed the PRISMA protocol. Results: A total of 27 papers were selected for this systematic review, covering the period from 2003 to 2023. The findings consistently indicate that ToM is globally affected in patients with manifest motor symptoms. In individuals without motor symptoms, impairments are focused on the affective dimensions of ToM. Conclusions: Based on our analysis, affective ToM could be considered a potential biomarker for HD. Therefore, it is recommended that ToM assessment be included as part of neuropsychological evaluation protocols in clinical settings. Suchinclusion could aid in the identification of early stages of the disease and provide new opportunities for treatment, particularly with emerging drugs like antisense oligomers. The Prospero registration number for this review is CRD42020209769.

Symptomatology of autism spectrum disorder in a population with neurofibromatosis type 1.

AIM: Difficulties in neurocognition and social interaction are the most prominent causes of morbidity and long-term disability in children with neurofibromatosis type 1 (NF1). Symptoms of attention-deficit-hyperactivity disorder (ADHD) have also been extensively recognized in NF1. However, systematic evaluation of symptoms of autism spectrum disorder (ASD) in children with NF1 has been limited. METHOD: We present a retrospective, cross-sectional study of the prevalence of symptoms of ASD and ADHD and their relationship in a consecutive series of 66 patients from our NF1 clinic. The Social Responsiveness Scale and the Vanderbilt ADHD Diagnostic Parent Rating Scale were used to assess symptoms of ASD and ADHD. RESULTS: Sixty-six participants (42 males, 24 females) were included in this study. Mean age at assessment was 10 years 11 months (SD 5 y 4 mo). Forty percent of our NF1 sample had raised symptom levels reaching clinical significance on the Social Responsiveness Scale (T ≥ 60), and 14% reached levels consistent with those seen in children with ASDs (T ≥ 75). These raised levels were not explained by NF1 disease severity or externalizing/internalizing behavioral disorders. There was a statistically significant relationship between symptoms of ADHD and ASD (χ(2) =9.11, df=1, p=0.003, φ=0.56). Particularly salient were the relationships between attention and hyperactivity deficits, with impairments in social awareness and social motivation. INTERPRETATION: We found that symptoms of ASD in our NF1 population were raised, consistent with previous reports. Further characterization of the specific ASD symptoms and their impact on daily function is fundamental to the development and implementation of effective interventions in this population, which will probably include a combination of medical and behavioral approaches.

Leading consumption patterns of psychoactive substances in Colombia: A deep neural network-based clustering-oriented embedding approach.

The number of health-related incidents caused using illegal and legal psychoactive substances (PAS) has dramatically increased over two decades worldwide. In Colombia, the use of illicit substances has increased up to 10.3%, while the consumption alcohol and tobacco has increased to 84% and 12%, respectively. It is well-known that identifying drug consumption patterns in the general population is essential in reducing overall drug consumption. However, existing approaches do not incorporate Machine Learning and/or Deep Data Mining methods in combination with spatial techniques. To enhance our understanding of mental health issues related to PAS and assist in the development of national policies, here we present a novel Deep Neural Network-based Clustering-oriented Embedding Algorithm that incorporates an autoencoder and spatial techniques. The primary goal of our model is to identify general and spatial patterns of drug consumption and abuse, while also extracting relevant features from the input data and identifying clusters during the learning process. As a test case, we used the largest publicly available database of legal and illegal PAS consumption comprising 49,600 Colombian households. We estimated and geographically represented the prevalence of consumption and/or abuse of both PAS and non-PAS, while achieving statistically significant goodness-of-fit values. Our results indicate that region, sex, housing type, socioeconomic status, age, and variables related to household finances contribute to explaining the patterns of consumption and/or abuse of PAS. Additionally, we identified three distinct patterns of PAS consumption and/or abuse. At the spatial level, these patterns indicate concentrations of drug consumption in specific regions of the country, which are closely related to specific geographic locations and the prevailing social and environmental contexts. These findings can provide valuable insights to facilitate decision-making and develop national policies targeting specific groups given their cultural, geographic, and social conditions.

Ancestry component as a major predictor of lithium response in the treatment of bipolar disorder.

BACKGROUND: Bipolar Disorder (BD) represents the seventh major cause of disability life-years-adjusted. Lithium remains as a first-line treatment, but clinical improvement occurs only in 30 % of treated patients. Studies suggest that genetics plays a major role in shaping the individual response of BD patients to lithium. METHODS: We used machine-learning techniques (Advance Recursive Partitioned Analysis, ARPA) to build a personalized prediction framework of BD lithium response using biological, clinical, and demographical data. Using the Alda scale, we classified 172 BD I-II patients as responders or non-responders to lithium treatment. ARPA methods were used to build individual prediction frameworks and to define variable importance. Two predictive models were evaluated: 1) demographic and clinical data, and 2) demographic, clinical and ancestry data. Model performance was assessed using Receiver Operating Characteristic (ROC) curves. RESULTS: The predictive model including ancestry yield the best performance (sensibility = 84.6 %, specificity = 93.8 % and AUC = 89.2 %) compared to the model without ancestry (sensibility = 50 %, Specificity = 94.5 %, and AUC = 72.2 %). This ancestry component best predicted lithium individual response. Clinical variables such as disease duration, the number of depressive episodes, the total number of affective episodes, and the number of manic episodes were also important predictors. CONCLUSION: Ancestry component is a major predictor and significantly improves the definition of individual Lithium response in BD patients. We provide classification trees with potential bench application in the clinical setting. While this prediction framework might be applied in specific populations, the used methodology might be of general use in precision and translational medicine.

A common genetic network underlies substance use disorders and disruptive or externalizing disorders.

Here we summarize evidence obtained by our group during the last two decades, and contrasted it with a review of related data from the available literature to show that behavioral syndromes involving attention deficit/hyperactivity disorder (ADHD), externalizing disorders, and substance-use disorder (SUD) share similar signs and symptoms (i.e., have a biological basis as common syndromes), physiopathological and psychopathological mechanisms, and genetic factors. Furthermore, we will show that the same genetic variants harbored in different genes are associated with different syndromes and that non-linear interactions between genetic variants (epistasis) best explain phenotype severity, long-term outcome, and response to treatment. These data have been depicted in our studies by extended pedigrees, where ADHD, externalizing symptoms, and SUD segregate and co-segregate. Finally, we applied here a new formal network analysis using the set of significantly replicated genes that have been shown to be either associated and/or linked to ADHD, disruptive behaviors, and SUD in order to detect significantly enriched gene categories for protein and genetic interactions, pathways, co-expression, co-localization, and protein domain similarity. We found that networks related to pathways involved in axon guidance, regulation of synaptic transmission, and regulation of transmission of nerve impulse are overrepresented. In summary, we provide compiled evidence of complex networks of genotypes underlying a wide phenotype that involves SUD and externalizing disorders.

Utilizing prospective sequence analysis of SHH, ZIC2, SIX3 and TGIF in holoprosencephaly probands to describe the parameters limiting the observed frequency of mutant gene×gene interactions.

Clinical molecular diagnostic centers routinely screen SHH, ZIC2, SIX3 and TGIF for mutations that can help to explain holoprosencephaly and related brain malformations. Here we report a prospective Sanger sequence analysis of 189 unrelated probands referred to our diagnostic lab for genetic testing. We identified 28 novel unique mutations in this group (15%) and no instances of deleterious mutations in two genes in the same subject. Our result extends that of other diagnostic centers and suggests that among the aggregate 475 prospectively sequenced holoprosencephaly probands there is negligible evidence for direct gene-gene interactions among these tested genes. We model the predictions of the observed mutation frequency in the context of the hypothesis that gene×gene interactions are a prerequisite for forebrain malformations, i.e. the "multiple-hit" hypothesis. We conclude that such a direct interaction would be expected to be rare and that more subtle genetic and environmental interactions are a better explanation for the clinically observed inter- and intra-familial variability.

ADGRL3 genomic variation implicated in neurogenesis and ADHD links functional effects to the incretin polypeptide GIP.

Attention deficit/hyperactivity disorder (ADHD) is the most common childhood neurodevelopmental disorder. Single nucleotide polymorphisms (SNPs) in the Adhesion G Protein-Coupled Receptor L3 (ADGRL3) gene are associated with increased susceptibility to developing ADHD worldwide. However, the effect of ADGRL3 non-synonymous SNPs (nsSNPs) on the ADGRL3 protein function is vastly unknown. Using several bioinformatics tools to evaluate the impact of mutations, we found that nsSNPs rs35106420, rs61747658, and rs734644, previously reported to be associated and in linkage with ADHD in disparate populations from the world over, are predicted as pathogenic variants. Docking analysis of rs35106420, harbored in the ADGLR3-hormone receptor domain (HRM, a common extracellular domain of the secretin-like GPCRs family), showed that HRM interacts with the Glucose-dependent insulinotropic polypeptide (GIP), part of the incretin hormones family. GIP has been linked to the pathogenesis of diabetes mellitus, and our analyses suggest a potential link to ADHD. Overall, the comprehensive application of bioinformatics tools showed that functional mutations in the ADGLR3 gene disrupt the standard and wild ADGRL3 structure, most likely affecting its metabolic regulation. Further in vitro experiments are granted to evaluate these in silico predictions of the ADGRL3-GIP interaction and dissect the complexity underlying the development of ADHD.

Executive function deficit in bipolar offspring: A neurocognitive endophenotype?

BACKGROUND: Recent studies in bipolar offspring (BO) showed that a low cognitive performance, especially executive function deficit, could be an early marker of bipolar disorder (BD). Nevertheless, these findings have not been replicated (specifically attentional control, flexibility, and working memory). In addition, most studies have focused on children and adolescents, but few studies analyze the executive function performance in BO adults. OBJECTIVE: Our goal was to compare the neurocognitive performance of BO with control parent-offspring (CO) in a sample that included various age groups. METHOD: We conducted a cohort study, including subjects between six to 30 years old. We evaluated 129 BO and 113 CO subjects using validated psychiatric diagnostic interviews and an extensive neuropsychological battery. RESULTS: Compared to the CO group, the BO group presented a lower performance in several executive functioning domains, mainly in tasks of attentional control, flexibility, and working memory. All age groups exhibited these findings. CONCLUSIONS: BO group presents executive function deficits, regardless of the age group: children, adolescents, and adults. This neurocognitive deficit should be accountable as a neurocognitive endophenotype candidate in BD.

Machine Learning Prediction of ADHD Severity: Association and Linkage to ADGRL3, DRD4, and SNAP25.

OBJECTIVE: To investigate whether single nucleotide polymorphisms (SNPs) in the ADGRL3, DRD4, and SNAP25 genes are associated with and predict ADHD severity in families from a Caribbean community. METHOD: ADHD severity was derived using latent class cluster analysis of DSM-IV symptomatology. Family-based association tests were conducted to detect associations between SNPs and ADHD severity latent phenotypes. Machine learning algorithms were used to build predictive models of ADHD severity based on demographic and genetic data. RESULTS: Individuals with ADHD exhibited two seemingly independent latent class severity configurations. SNPs harbored in DRD4, SNAP25, and ADGRL3 showed evidence of linkage and association to symptoms severity and a potential pleiotropic effect on distinct domains of ADHD severity. Predictive models discriminate severe from non-severe ADHD in specific symptom domains. CONCLUSION: This study supports the role of DRD4, SNAP25, and ADGRL3 genes in outlining ADHD severity, and a new prediction framework with potential clinical use.