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Dive into the research topics where Machiel J. Zwarts is active.

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Featured researches published by Machiel J. Zwarts.


Nature Genetics | 2009

Genome-wide association study identifies 19p13.3 (UNC13A) and 9p21.2 as susceptibility loci for sporadic amyotrophic lateral sclerosis

Michael A. van Es; Jan H. Veldink; Christiaan G.J. Saris; Hylke M. Blauw; Paul W.J. van Vught; Anna Birve; Robin Lemmens; Helenius J. Schelhaas; Ewout J.N. Groen; Mark H. B. Huisman; Anneke J. van der Kooi; Marianne de Visser; Caroline Dahlberg; Karol Estrada; Fernando Rivadeneira; Albert Hofman; Machiel J. Zwarts; Perry T.C. van Doormaal; Dan Rujescu; Eric Strengman; Ina Giegling; Pierandrea Muglia; Barbara Tomik; Agnieszka Slowik; André G. Uitterlinden; Corinna Hendrich; Stefan Waibel; Thomas Meyer; Albert C. Ludolph; Jonathan D. Glass

We conducted a genome-wide association study among 2,323 individuals with sporadic amyotrophic lateral sclerosis (ALS) and 9,013 control subjects and evaluated all SNPs with P < 1.0 × 10−4 in a second, independent cohort of 2,532 affected individuals and 5,940 controls. Analysis of the genome-wide data revealed genome-wide significance for one SNP, rs12608932, with P = 1.30 × 10−9. This SNP showed robust replication in the second cohort (P = 1.86 × 10−6), and a combined analysis over the two stages yielded P = 2.53 × 10−14. The rs12608932 SNP is located at 19p13.3 and maps to a haplotype block within the boundaries of UNC13A, which regulates the release of neurotransmitters such as glutamate at neuromuscular synapses. Follow-up of additional SNPs showed genome-wide significance for two further SNPs (rs2814707, with P = 7.45 × 10−9, and rs3849942, with P = 1.01 × 10−8) in the combined analysis of both stages. These SNPs are located at chromosome 9p21.2, in a linkage region for familial ALS with frontotemporal dementia found previously in several large pedigrees.


Muscle & Nerve | 2003

Multichannel surface EMG: Basic aspects and clinical utility

Machiel J. Zwarts; Dick F. Stegeman

The generation of the surface electromyogram (sEMG) is described with regard to the properties of the single muscle fiber action potential as source, the physical aspects of volume conduction and recording configuration, and the properties and firing pattern of motor units (MUs). The spatial aspect of the motor unit action potential (MUP) is emphasized in relation to the results of high‐density, multichannel sEMG measurements. The endplate zone, depth, size, and position of MUs can be estimated. The use of muscle fiber conduction velocity measurements in channelopathies and the changes in pathological fatigue are described. Using the unique patterns of spatial spread of MUPs over the skin (MU fingerprint), MU classification and the determination of firing moments is done noninvasively. Clinical applications of high‐density sEMG measurements are reviewed. Emerging possibilities provided by MUP size and fingerprint measurements in neuromuscular disease and motor control are discussed. We conclude that multichannel sEMG adds unique, and sometimes indispensable, spatial information to our knowledge of the motor unit. Muscle Nerve 28: 1–17, 2003


Muscle & Nerve | 2008

Muscle ultrasound in neuromuscular disorders.

Sigrid Pillen; Ilse M. P. Arts; Machiel J. Zwarts

Muscle ultrasound is a useful tool in the diagnosis of neuromuscular disorders, as these disorders result in muscle atrophy and intramuscular fibrosis and fatty infiltration, which can be visualized with ultrasound. Several prospective studies have reported high sensitivities and specificities in the detection of neuromuscular disorders. Although not investigated in large series of patients, different neuromuscular disorders tend to show specific changes on muscle ultrasound, which can be helpful in differential diagnosis. For example, Duchenne muscular dystrophy results in a severe, homogeneous increase of muscle echo intensity with normal muscle thickness, whereas spinal muscular atrophy shows an inhomogeneous increase of echo intensity with severe atrophy. A major advantage of muscle ultrasound, compared to other imaging techniques, is its ability to visualize muscle movements, such as muscle contractions and fasciculations. This study reviews the possibilities and limitations of ultrasound in muscle imaging and its value as a diagnostic tool in neuromuscular disorders. Muscle Nerve, 2008


Ultrasound in Medicine and Biology | 2009

Skeletal Muscle Ultrasound: Correlation Between Fibrous Tissue and Echo Intensity

Sigrid Pillen; Ramon O. Tak; Machiel J. Zwarts; Martin Lammens; Kiek Verrijp; Ilse M.P. Arts; Jeroen van der Laak; Peter M. Hoogerbrugge; Baziel G.M. van Engelen; Aad Verrips

In this study, we examined the correlation between muscle ultrasound and muscle structure. Echo intensity (EI) of 14 muscles of two golden retriever muscular dystrophy dogs was correlated to the percentage interstitial fibrous tissue and fat in muscle biopsy. A significant correlation between interstitial fibrous tissue and EI was found (r = 0.87; p < 0.001). The separate influence of interstitial fat on muscle EI could not be established as only little fat was present. We conclude that fibrous tissue causes increased muscle EI. The high correlation between interstitial fibrous tissue and EI makes ultrasound a reliable method to determine severity of structural muscle changes.


Muscle & Nerve | 2010

Normal values for quantitative muscle ultrasonography in adults.

Ilse M.P. Arts; Sigrid Pillen; H. Jurgen Schelhaas; Sebastiaan Overeem; Machiel J. Zwarts

Ultrasonography can detect structural muscle changes caused by neuromuscular disease. Quantitative analysis is the preferred method to determine if ultrasound findings are within normal limits, but normative data are incomplete. The purpose of this study was to provide normative muscle ultrasonography data for muscle thickness and echo intensity for five different muscle groups in adults. Bilateral scans of the sternocleidomastoid, biceps brachii/brachialis, forearm flexor group, quadriceps femoris, and tibialis anterior were made in 95 volunteers, aged 17–90 years. Both muscle thickness and echo intensity showed gender differences and a muscle‐specific non‐linear correlation with age. The muscles of the upper extremities showed right–left differences. These data demonstrate the effect of age on muscle characteristics and provide normative values that can be used in clinical practice. Muscle Nerve, 2010


Muscle & Nerve | 2003

Quantitative ultrasonography of skeletal muscles in children: normal values.

R.R. Scholten; Sigrid Pillen; Aad Verrips; Machiel J. Zwarts

The purpose of this study was to establish normal values of muscle thickness, ratio of muscle thickness to subcutaneous fat thickness, and muscle echo intensity in children between 11 weeks and 16 years of age. Transverse scans of four muscles were made by standardized real‐time ultrasound examination. The scans were digitized, and mean echo intensity was measured using gray‐scale analysis. A multiple regression equation was used to study which independent parameter (age, height, weight, or sex) influenced the variables for each muscle. Muscle thickness depended on the childs weight. The other parameters did not significantly influence muscle thickness after correction for weight. The ratio of muscle thickness to subcutaneous fat thickness depended on age. Echo intensity showed no correlation with either of the variables. As a result, all normal values, including the equation to calculate them, are described. These normal data may help to determine the diagnostic value of muscle ultrasound in children with suspected neuromuscular disease. Muscle Nerve 27: 693–698, 2003


Annals of Neurology | 2009

Neuromuscular involvement in various types of Ehlers-Danlos syndrome.

Nicol C. Voermans; Nens van Alfen; Sigrid Pillen; Martin Lammens; Joost Schalkwijk; Machiel J. Zwarts; Iris A.L.M. van Rooij; B.C.J. Hamel; Baziel G.M. van Engelen

Ehlers–Danlos syndrome (EDS) is a clinically and genetically heterogeneous group of heritable connective tissue disorders characterized by joint hypermobility, skin hyperextensibility, and tissue fragility. Muscle involvement is plausible based on recently discovered interactions between muscle cells and extracellular matrix molecules; however, muscle symptoms are only sporadically reported. We designed a cross‐sectional study to find out whether neuromuscular features are part of EDS.


Muscle & Nerve | 2003

Quantitative skeletal muscle ultrasonography in children with suspected neuromuscular disease

Sigrid Pillen; R.R. Scholten; Machiel J. Zwarts; Aad Verrips

We determined prospectively the diagnostic value of quantitative ultrasonography in detecting neuromuscular disorders in children. Ultrasonographic scans of four muscles were made in 36 children with symptoms or signs suggestive of neuromuscular disease, such as muscle weakness and hypotonia. The muscle thickness, ratio of muscle thickness to subcutaneous fat thickness, and echo intensity were determined in each muscle. The echo intensity was measured using computer‐assisted gray‐scale analysis. Thirteen of the 36 patients had a neuromuscular disorder (6 a myopathy and 7 a neuropathy). Differentiation between neuromuscular diseases and nonneuromuscular diseases could be made on the basis of echo intensities with a sensitivity of 92%, a specificity of 90%, a positive predictive value of 86%, and a negative predictive value of 95%. We conclude that computer‐assisted quantitative analysis of muscle echo intensity is a reliable method to discriminate between neuromuscular and nonneuromuscular diseases in children. Muscle Nerve 27: 699–705, 2003


European Journal of Applied Physiology | 2003

Relative contributions of central and peripheral factors to fatigue during a maximal sustained effort

Maartje L. Schillings; Wouter Hoefsloot; Dick F. Stegeman; Machiel J. Zwarts

Local muscle fatigue can originate from both peripheral and central factors. The relative contribution of these factors in the course of a fatiguing contraction in 20 healthy subjects was determined. While subjects made a 2-min sustained maximal voluntary contraction (MVC) of the biceps brachii, muscle fibre conduction velocity (MFCV) was determined with surface electromyography (SEMG) as a representation of developing peripheral fatigue. To quantify the amount of peripheral fatigue, the force development following a train of electrical stimuli on the endplate before and after the contraction were compared. To measure force loss caused by central factors, superimposed electrical stimulation was used during the contraction. By two different methods the influence of peripheral fatigue on the superimposed force responses was taken into account. The first method compared the force response with the actual voluntary force, the second –which seemed more valid – used an estimation of peripheral fatigue based on linear interpolation between the force responses during rest before and after sustained contraction. During the contraction, voluntary force decreased to 38%. Peripheral fatigue was responsible for the larger part of this decline (89%). The other part, which was calculated as 12%, was caused by an increase of central activation failure. The decline of MFCV indicated that peripheral fatigue increased predominantly during the first half of the contraction and stayed at a constant level during the latter part. In contrast, central fatigue mainly induced a force decrease in the second part of the contraction. The different mechanisms which could be responsible for this change of emphasis from peripheral to central factors are discussed.


Clinical Neurophysiology | 2007

Experienced and physiological fatigue in neuromuscular disorders

M.L. Schillings; Joke S. Kalkman; H.M.H.A. Janssen; B.G.M. van Engelen; Gijs Bleijenberg; Machiel J. Zwarts

OBJECTIVE Fatigue has been described as a typical symptom of neurological diseases. It might be caused both by changes at the peripheral and at the central level. This study measured the level of experienced fatigue and physiological correlates of fatigue in three genetically defined neuromuscular disorders. METHODS Sixty-five facioscapulohumeral dystrophy (FSHD), 79 classical myotonic dystrophy (DM), 73 hereditary motor and sensory neuropathy type I (HMSN) patients and 24 age-matched healthy controls made a 2-min sustained maximal voluntary contraction of the biceps brachii muscle. Experienced fatigue at the current moment was assessed with the abbreviated fatigue questionnaire just before the physiological measurement. Peripheral fatigue was quantified by comparing the amplitudes of an initial and a final stimulated force response during rest. Muscle fibre conduction velocity was determined from a 5-channel surface EMG recording in order to show peripheral changes during the contraction. Central aspects of fatigue were measured using superimposed electrical endplate stimulation. RESULTS Patients showed an increased level of experienced fatigue. Total physiological and peripheral fatigue were smaller in patients compared to controls, and central fatigue was normal. The most interesting result of this study was the presence of a large central activation failure (CAF) in all groups of neuromuscular patients; they showed CAF values of 36-41% already directly at the start of sustained contraction, whereas the control group showed only 12%. CAF slightly correlated with the level of experienced fatigue just before the test. CONCLUSIONS The cause of the large CAF in patients is unclear. Reduced concentration, motivation or effort can lead to lower central activation. In neuromuscular patients especially fear of physical activity or fear to damage the muscle or nerve tissue may contribute. Besides, also physiological feedback mechanisms or changes at the motocortical level may be a cause of reduced central activation. SIGNIFICANCE For the clinician it is important to know that experienced fatigue is part of the clinical spectrum of neuromuscular patients. Besides, the weakness in these patients is aggravated by reduced central activation. Potentially, both problems could be subject of an intervention.

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Dick F. Stegeman

Radboud University Nijmegen

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Sigrid Pillen

Radboud University Nijmegen Medical Centre

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Gea Drost

University Medical Center Groningen

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Sebastiaan Overeem

Eindhoven University of Technology

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Gijs Bleijenberg

Radboud University Nijmegen

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Ilse M.P. Arts

Radboud University Nijmegen Medical Centre

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Bert U. Kleine

Radboud University Nijmegen Medical Centre

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H. Jurgen Schelhaas

Radboud University Nijmegen Medical Centre

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