Browsing by Author "Villaman, Camilo"
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Publication Copy Number Variation Analysis from SNP Genotyping Microarrays in Large Cohorts of Neurological Disorders(2022) Pérez, Eduardo; Niestroj, Lisa; Martínez, Miguel; Villaman, Camilo; Irem, Elif; Lal, Dennis; Mata, IgnacioCopy number variants (CNVs) are a major source of genetic variation in the human genome, and they are highly heterogeneous in type, size, and frequency. CNVs represent the largest portion of genomic variation between humans, and a subset of CNVs has been associated with multiple rare and common neurological disorders. Although recent sequencing-based methods deliver increased resolution and greater power in detecting CNVs, SNP genotyping microarrays still provide a scalable opportunity to analyze CNVs in large cohorts of neurological disorders. In the past 15 years, case-control genome-wide association studies and population-based biobanks have widely used SNP genotyping microarrays to understand the heritability of common variants. As a result, massive amounts of SNP microarray data are available and provide a costefficient opportunity to repurpose the data and study large and rare CNVs. Here we describe a workflow to detect and analyze CNVs from SNP genotyping microarrays. We describe established CNV quality control procedures, CNV downstream analyses, case-control burden analysis, and validation protocols with particular focus on nervous system disorders and non-European datasets.Publication Polygenic score analysis identifies distinct genetic risk profiles in Alzheimer’s disease comorbidities(2025) Hernández, Carlos F.; Villaman, Camilo; Leu, Costin; Lal, Dennis; Mata, Ignacio; Klein, Andrés; Pérez-Palma, EduardoAlzheimer’s disease (AD) is usually accompanied by comorbidities such as type 2 diabetes (T2D), epilepsy, major depressive disorder (MDD), and migraine headaches (MH) that can significantly affect patient management and progression. As AD, these comorbidities have their own cumulative common genetic risk component that can be explored in a single individual through polygenic scores. Utilizing data from the UK Biobank, we investigated the correlation between polygenic scores (PGS) for these comorbidities and their actual presentation in AD patients. We show that individuals with higher PGS values showed an elevated risk of developing T2D (OR 2.1, p = 1.07 × 10−11) and epilepsy (OR 1.5, p = 0.0176). High T2D-PGS is also associated with an earlier AD onset in individuals at high genetic risk for AD (AD-PGS). In contrast, no significant genetic associations were found for MDD and MH. Our findings show distinct common genetic risk factors for T2D and epilepsy carried by AD patients that are associated with increased prevalence and earlier disease onset. These results highlight the contribution of common genetic variation to the broader clinical landscape of AD and will contribute to future tailored patient management strategies for individuals at high genetic risk.Publication Polygenic scores contribution to Parkinson's disease comorbidities(2025) Hernández, Carlos; Villaman, Camilo; Tejos, Cristian; Repetto, Gabriela; Leu, Costin; Lal, Dennis; Mata, Ignacio; Klein, Andrés; Pérez Palma, EduardoComorbidities are common in Parkinson's disease and significantly impact the disease progression and management. While polygenic scores have been widely used to assess genetic risk for complex diseases, their role in comorbidity presentation in Parkinson's disease remains unclear. This study investigates whether genetic predisposition to comorbidities, as measured by polygenic scores, differs between individuals with Parkinson's disease and the general population and explores how genetic risk influences disease onset and sex-related differences. We analysed data from 4144 individuals with Parkinson's disease and 370 480 individuals from the general population in the UK Biobank, focusing on four comorbidities with high-quality genome-wide association study data: Type 2 diabetes, major depressive disorder, migraine headaches and epilepsy. We first compared polygenic score distributions between individuals with Parkinson's disease and the general population. While our findings indicate that comorbidities and polygenic risk scores do not significantly differ between individuals with Parkinson's disease and the general population, we show an association with disease onset and sex-specific differences. Individuals with earlier disease onset (50-70 years old) had higher genetic risk for major depressive disorder (odds ratio: 2.19, P-value: 1.27 × 10⁻¹⁵) and epilepsy (odds ratio: 1.58, P-value: 0.00845). Additionally, a female participant with Parkinson's disease exhibited higher genetic risk scores for major depressive disorder (odds ratio: 1.5, P-value: 0.0119) and migraine headaches (odds ratio: 2.1, P-value: 0.0155), while a male participant displayed higher genetic risk scores for Type 2 diabetes (odds ratio: 2.7, P-value: 2.11 × 10⁻¹⁷). Comorbidity-polygenic score did not differ between people with versus without Parkinson's disease, yet within Parkinson's disease, a higher genetic burden for specific comorbidities was linked to earlier onset and sex-specific presentation, implicating common variants as modifiers of clinical heterogeneity rather than the primary disease risk. These results enhance our understanding of the genetic influences shaping the broader clinical presentation of Parkinson's disease and highlight the need for further research into the interplay between genetic risk factors, comorbidities and disease heterogeneity.Publication SCN9A should not be considered an epilepsy gene; Refuting a gene–disease association(2026) Ghanty, Ismael; Perez-Palma, Eduardo; Villaman, Camilo; Stobo, Daniel; Symonds, Joseph; Zuberi, Sameer; Lal, Dennis; Brunklaus, AndreasObjective The SCN9A gene is primarily expressed in nociceptive pathways within the peripheral nervous system, and pathogenic variants are associated with human pain disorders. In recent years, several studies have proposed SCN9A as a monogenic cause of epilepsy. Our objective was to critically appraise the SCN9A–epilepsy gene–disease relationship. Methods We assessed “epilepsy-associated” SCN9A variants from four sources: (1) the literature up to December 2023 (n = 27), (2) epilepsy patients referred for genetic testing at a regional service in Glasgow, UK over a 5-year period (n = 30), (3) the Human Genetics Mutation Database (n = 25), and (4) ClinVar (n = 1546). The latter two are genome-wide variant databases, accepting submissions from genetic laboratories and research groups. We checked whether each SCN9A variant is present in the Genome Aggregation Database (gnomAD) V4 (a reference population database for variant interpretation), and classified its pathogenicity based on the American College of Molecular Genetics and Genomics/Association of Molecular Pathologists guidelines. Results Only three SCN9A variants were classified as “likely pathogenic,” of which two were identified in healthy individuals in gnomAD. A total of 1540 of the 1546 SCN9A variants in ClinVar labeled as being associated with epilepsy were also reported in association with hereditary sensory and autonomic neuropathy. No further clinical data were provided in 1482 of these submissions. Significance There is no convincing genetic evidence to support SCN9A as a causative epilepsy gene. As such, the inclusion of SCN9A in epilepsy genetic testing panels should be reassessed. Research centers and genetic testing laboratories should be rigorous and consistent in their submissions to variant databases.