Publications by authors named "Kajsa Brolin"

Article Synopsis
  • Copy Number Variations (CNVs) are crucial in understanding complex diseases and vary across different populations, necessitating large sample studies for accurate analysis.
  • The CNV-Finder pipeline utilizes deep learning, specifically Long Short-Term Memory (LSTM) networks, to streamline the identification of CNVs in specific genomic areas, making subsequent analyses like genome sequencing more efficient.
  • The tool has been validated with data from various cohorts, focusing on genes related to neurological diseases, and includes an interactive web application for researchers to visualize and refine their findings based on model predictions.
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Variants in GBA1 are important genetic risk factors in Parkinson's disease (PD). GBA1 T369M has been linked to an ∼80 % increased PD risk but the reports are conflicting and the relevance of GBA1 variants in different populations varies. A lack of association between T369M and PD in the Swedish population was recently reported but needs further validation.

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Variants in are important genetic risk factors in Parkinson's disease (PD). T369M has been linked to an ~80% increased PD risk but the reports are conflicting and the relevance of variants in different populations varies. A lack of association between T369M and PD in the Swedish population was recently reported but needs further validation.

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Introduction: Parkinson's disease (PD) is the second most common neurodegenerative disorder, increasing both in terms of prevalence and incidence. To date, only symptomatic treatment is available, highlighting the need to increase knowledge on disease etiology in order to develop new therapeutic strategies. Hemizygosity for the gene Engrailed-1 (), encoding a conserved transcription factor essential for the programming, survival, and maintenance of midbrain dopaminergic neurons, leads to progressive nigrostriatal degeneration, motor impairment and depressive-like behavior in SwissOF1 (OF1).

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Article Synopsis
  • * A virtual 3-day hackathon brought together 49 early-career scientists from 12 countries, focusing on building tools and pipelines specifically for PD research, with each team working on one of nine distinct projects.
  • * The hackathon not only generated resources to enhance research but also provided training and networking opportunities, ultimately fostering creative problem-solving and collaboration essential for emerging researchers in data science.
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  • * A genome-wide association study identified five genetic risk loci for RBD near specific genes (SNCA, GBA, TMEM175, INPP5F, and SCARB2), suggesting a genetic basis for the disorder.
  • * Further analysis indicates that certain genes, like SNCA-AS1, show different expression levels in various brain regions affected by RBD, paving the way for recognizing RBD as a distinct subtype of alpha-synucleinopathy for potential early interventions.
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Parkinson's disease (PD) is a complex neurodegenerative condition in which genetic and environmental factors interact to contribute to its etiology. Remarkable progress has been made in deciphering disease etiology through genetic approaches, but there is limited data about how environmental and genetic factors interact to modify penetrance, risk, and disease severity. Here, we provide insights into environmental modifiers of PD, discussing precedents from other neurological and non-neurological conditions.

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Background: Risk factors for Parkinson's disease (PD) can be more or less relevant to a population due to population-specific genetic architecture, local lifestyle habits, and environmental exposures. Therefore, it is essential to study PD at a local, regional, and continental scale in order to increase the knowledge on disease etiology.

Objective: We aimed to investigate the contribution of genetic and environmental factors to PD in a new Swedish case-control cohort.

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Article Synopsis
  • Parkinson's disease (PD) involves genetic factors, with some genes linked to the disease, yet these explain only part of the familial risk.
  • Research into the RIC3 gene has suggested it might be connected to PD in Indian populations, but findings have been inconsistent across studies.
  • In a large analysis of European cohorts and additional data from Latin American and East Asian populations, no significant association between RIC3 and PD was found, highlighting the need for further investigation in diverse populations, particularly South Asians.
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Background: Parkinson's disease (PD) is a neurodegenerative disease with an often complex component identifiable by genome-wide association studies. The most recent large-scale PD genome-wide association studies have identified more than 90 independent risk variants for PD risk and progression across more than 80 genomic regions. One major challenge in current genomics is the identification of the causal gene(s) and variant(s) at each genome-wide association study locus.

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Objective: To determine the frequency of mutations known to cause autosomal dominant Parkinson disease (PD) in a series with more than 10% of Sweden's estimated number of PD patients.

Methods: The Swedish Parkinson Disease Genetics Network was formed as a national multicenter consortium of clinical researchers who together have access to DNA from a total of 2,206 PD patients; 85.4% were from population-based studies.

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Parkinson's disease (PD) is a common, progressive neurodegenerative disease, which typically presents itself with a range of motor symptoms, like resting tremor, bradykinesia, and rigidity, but also non-motor symptoms such as fatigue, constipation, and sleep disturbance. Neuropathologically, PD is characterized by loss of dopaminergic cells in the substantia nigra pars compacta (SNpc) and Lewy bodies, neuronal inclusions containing α-synuclein (α-syn). Mutations and copy number variations of , the gene encoding α-syn, are linked to familial PD and common gene variants are associated to idiopathic PD.

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