Uveitis, defined as inflammation of the uveal tract of the eye, is a leading cause of blindness and visual impairment throughout the world. The etiology of uveitis is complex, and autoimmunity plays a major role in its pathogenesis. Intermediate uveitis (IU), a subtype of ocular inflammation, has been associated with systemic autoimmune disorders, specifically with multiple sclerosis (MS). This article reports a rare three-generation family with several members affected by IU (four siblings) and comorbid MS (two siblings fulfilling MS diagnostic criteria and a third sibling presenting some neurological symptoms). Based on the clinical findings, we captured and sequenced whole exomes of seven pedigree members (affected and unaffected). Using a recessive model of transmission with full penetrance, we applied genetic linkage analysis to define minimal critical regions (MCRs) in suggestive or nominal regions of linkage. In these MCRs, we defined functional (some pathogenic), novel, and rare mutations that segregated as homozygous in affected and heterozygous in unaffected family members. The genes harboring these mutations, including DGKI, TNFRSF10A, GNGT1, CPAMD8, and BAFF, which are expressed in both eye and brain tissues and/or are related to autoimmune diseases, provide new avenues to evaluate the inherited causes of these devastating autoimmune conditions.

Attention deficit hyperactivity disorder (ADHD) is a highly heritable neurobehavioral disorder that affects children worldwide, with detrimental long-term consequences in affected individuals. ADHD-affected patients display visual–motor and visuospatial abilities and skills that depart from those exhibited by non-affected individuals and struggle with perceptual organization, which might partially explain impulsive responses. Endophenotypes (quantifiable or dimensional constructs that are closely related to the root cause of the disease) might provide a more powerful and objective framework for dissecting the underlying neurobiology of ADHD than that of categories offered by the syndromic classification. In here, we explore the potential presence of the linkage and association of single-nucleotide polymorphisms (SNPs), harbored in genes implicated in the etiology of ADHD (ADGRL3, DRD4, and FGF1), with cognitive endophenotypes related to working memory and perceptual organization in 113 nuclear families. These families were ascertained from a geographical area of the Caribbean coast, in the north of Colombia, where the community is characterized by its ethnic diversity and differential gene pool. We found a significant association and linkage of markers ADGRL3-rs1565902, DRD4-rs916457 and FGF1-rs2282794 to neuropsychological tasks outlining working memory and perceptual organization such as performance in the digits forward and backward, arithmetic, similarities, the completion of figures and the assembly of objects. Our results provide strong support to understand ADHD as a combination of working memory and perceptual organization deficits and highlight the importance of the genetic background shaping the neurobiology, clinical complexity, and physiopathology of ADHD. Further, this study supplements new information regarding an ethnically diverse community with a vast African American contribution, where ADHD studies are scarce.

Presented here are five members of a family that was ascertained from an isolated, consanguineous, indigenous Amerindian community in Colombia that was affected with calpain 3-related, limb-girdle muscular dystrophy type R1. These patients are homozygous for a unique and novel deletion of four bases (TGCC) in exon 3 of the calpain 3 gene (CAPN3) (NM_000070.2; NP_000061.1) (g.409_412del). The mutation site occurs at the CysPc protein domain, triggering a modified truncated protein structure and affecting motifs within the calpain-like thiol protease family (peptidase family C2) region. The patients reported here developed a very severe phenotype with primary contractures, spinal rigidity in the early stages of the disease, and bilateral talipes equinovarus (clubfoot) in the most affected patients who had the selective involvement of their extremities' distal muscles in a way that resembled Emery-Dreifuss syndrome. We recommend mandatory screening for calpainopathy in all patients with an Emery-Dreifuss-like syndrome or those presenting a non-congenital illness with primary contractures and who, because of other data, are suspected of having muscular dystrophy.

Machine learning (ML) algorithms are widely used to develop predictive frameworks. Accurate prediction of Alzheimer’s disease (AD) age of onset (ADAOO) is crucial to investigate potential treatments, follow-up, and therapeutic interventions. Although genetic and non-genetic factors affecting ADAOO were elucidated by other research groups and ours, the comprehensive and sequential application of ML to provide an exact estimation of the actual ADAOO, instead of a high-confidence-interval ADAOO that may fall, remains to be explored. Here, we assessed the performance of ML algorithms for predicting ADAOO using two AD cohorts with early-onset familial AD and with late-onset sporadic AD, combining genetic and demographic variables. Performance of ML algorithms was assessed using the root mean squared error (RMSE), the R-squared (R2), and the mean absolute error (MAE) with a 10-fold cross-validation procedure. For predicting ADAOO in familial AD, boosting-based ML algorithms performed the best. In the sporadic cohort, boosting-based ML algorithms performed best in the training data set, while regularization methods best performed for unseen data. ML algorithms represent a feasible alternative to accurately predict ADAOO with little human intervention. Future studies may include predicting the speed of cognitive decline in our cohorts using ML.

Human Immunodeficiency Virus type 1 (HIV-1) infection is a chronic disease that affects ~40 million people worldwide. HIV-associated neurocognitive disorders (HAND) are common in individuals with HIV-1 Infection, and represent a recent public health problem. Here we evaluate the performance of a recently proposed short protocol for detecting HAND by studying 60 individuals with HIV-1-Infection and 60 seronegative controls from a Caribbean community in Barranquilla, Colombia. The short evaluation protocol used significant neuropsychological tests from a previous study of asymptomatic HIV-1 infected patients and a group of seronegative controls. Brief screening instruments, i.e., the Mini-mental State Examination (MMSE) and the International HIV Dementia Scale (IHDS), were also applied. Using machine-learning techniques, we derived predictive models of HAND status, and evaluated their performance with the ROC curves. The proposed short protocol performs exceptionally well yielding sensitivity, specificity, and overall prediction values >90%, and better predictive capacity than that of the MMSE and IHDS. Community-specific cut-off values for HAND diagnosis, based on the MMSE and IHDS, make this protocol suitable for HAND screening in individuals from this Caribbean community. This study shows the effectivity of a recently proposed short protocol to detect HAND in individuals with asymptomatic HIV-1-Infection. The application of community-specific cut-off values for HAND diagnosis in the clinical setting may improve HAND screening accuracy and facilitate patients’ treatment and follow-up. Further studies are needed to assess the performance of this protocol in other Latin American populations.