Clinical and genetic data of Huntington disease in Moroccan patients

Background: Huntington's disease (HD) occurs worldwide with prevalence varying from 0.1 to 10 /100,000 depending of the ethnic origin. Since no data is available in the Maghreb population, the aim of this study is to describe clinical and genetic characteristics of Huntington patients of Moroccan origin.Methods: Clinical and genetics data of 21 consecutive patients recruited from 2009 to 2014 from the outpatient clinic of six medical centers were analyzed. Statistical analysis was performed using descriptive statistics.Results: Twenty one patients from 17 families were diagnosed positive for the IT15 gene CAG expansion. Clinical symptoms were predominantly motor (19/21). Twelve patients had psychiatric and behavioral disorders, and 11 patients had cognitive disorders essentially of memory impairment. Analysis of genetic results showed that 5 patients had reduced penetrant (RP) alleles and 16 had fully penetrant (FP) alleles. The mean CAG repeat length in patients with RP alleles was 38.4 ± 0.54, and 45.37 ± 8.30 in FP alleles. The age of onset and the size of the CAG repeat length showed significant inverse correlation (p <0.001, r = -0.754).Conclusion: Clinical and genetic data of Moroccan patients are similar to those of Caucasian populations previously reported in the literature.Keywords: Huntington disease/diagnosis, Huntington disease/epidemiology, Huntington disease/genetics, Trinucleotide repeat expansio

Clinical and genetic data of Huntington disease in Moroccan patients

Background: Huntington's disease (HD) occurs worldwide with prevalence varying from 0.1 to 10 /100,000 depending of the ethnic origin. Since no data is available in the Maghreb population, the aim of this study is to describe clinical and genetic characteristics of Huntington patients of Moroccan origin. Methods: Clinical and genetics data of 21 consecutive patients recruited from 2009 to 2014 from the outpatient clinic of six medical centers were analyzed. Statistical analysis was performed using descriptive statistics. Results: Twenty one patients from 17 families were diagnosed positive for the IT15 gene CAG expansion. Clinical symptoms were predominantly motor (19/21). Twelve patients had psychiatric and behavioral disorders, and 11 patients had cognitive disorders essentially of memory impairment. Analysis of genetic results showed that 5 patients had reduced penetrant (RP) alleles and 16 had fully penetrant (FP) alleles. The mean CAG repeat length in patients with RP alleles was 38.4 \ub1 0.54, and 45.37 \ub1 8.30 in FP alleles. The age of onset and the size of the CAG repeat length showed significant inverse correlation (p <0.001, r = -0.754). Conclusion: Clinical and genetic data of Moroccan patients are similar to those of Caucasian populations previously reported in the literature

An autosomal recessive leucoencephalopathy with ischemic stroke, dysmorphic syndrome and retinitis pigmentosa maps to chromosome 17q24.2-25.3

Background Single-gene disorders related to ischemic stroke seem to be an important cause of stroke in young patients without known risk factors. To identify new genes responsible of such diseases, we studied a consanguineous Moroccan family with three affected individuals displaying hereditary leucoencephalopathy with ischemic stroke, dysmorphic syndrome and retinitis pigmentosa that appears to segregate in autosomal recessive pattern. Methods All family members underwent neurological and radiological examinations. A genome wide search was conducted in this family using the ABI PRISM linkage mapping set version 2.5 from Applied Biosystems. Six candidate genes within the region linked to the disease were screened for mutations by direct sequencing. Results Evidence of linkage was obtained on chromosome 17q24.2-25.3. Analysis of recombination events and LOD score calculation suggests linkage of the responsible gene in a genetic interval of 11 Mb located between D17S789 and D17S1806 with a maximal multipoint LOD score of 2.90. Sequencing of seven candidate genes in this locus, ATP5H, FDXR, SLC25A19, MCT8, CYGB, KCNJ16 and GRIN2C, identified three missense mutations in the FDXR gene which were also found in a homozygous state in three healthy controls, suggesting that these variants are not disease-causing mutations in the family. Conclusion A novel locus for leucoencephalopathy with ischemic stroke, dysmorphic syndrome and retinitis pigmentosa has been mapped to chromosome 17q24.2-25.3 in a consanguineous Moroccan family

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Deep Brain Stimulation in Moroccan Patients With Parkinson's Disease: The Experience of Neurology Department of Rabat

Introduction: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is known as a therapy of choice of advanced Parkinson's disease. The present study aimed to assess the beneficial and side effects of STN DBS in Moroccan Parkinsonian patients.Material and Methods: Thirty five patients underwent bilateral STN DBS from 2008 to 2016 in the Rabat University Hospital. Patients were assessed preoperatively and followed up for 6 to 12 months using the Unified Parkinson's Disease Rating Scale in four conditions (stimulation OFF and ON and medication OFF and ON), the levodopa-equivalent daily dose (LEDD), dyskinesia and fluctuation scores and PDQ39 scale for quality of life (QOL). Postoperative side effects were also recorded.Results: The mean age at disease onset was 42.31 ± 7.29 years [28–58] and the mean age at surgery was 54.66 ± 8.51 years [34–70]. The median disease duration was 11.95 ± 4.28 years [5–22]. Sixty-three percentage of patients were male. 11.4% of patients were tremor dominant while 45.71 showed akinetic-rigid form and 42.90 were classified as mixed phenotype. The LEDD before surgery was 1200 mg/day [800-1500]. All patients had motor fluctuations whereas non-motor fluctuations were present in 61.80% of cases. STN DBS decreased the LEDD by 51.72%, as the mean LEDD post-surgery was 450 [188-800]. The UPDRS-III was improved by 52.27%, dyskinesia score by 66.70% and motor fluctuations by 50%, whereas QOL improved by 27.12%. Post-operative side effects were hypophonia (2 cases), infection (3 cases), and pneumocephalus (2 cases).Conclusion: Our results showed that STN DBS is an effective treatment in Moroccan Parkinsonian patients leading to a major improvement of the most disabling symptoms (dyskinesia, motor fluctuation) and a better QOL

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe