Institute of Medical Genetics

H̱olon, Israel

Institute of Medical Genetics

H̱olon, Israel
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News Article | April 25, 2017

Up to 80% of people in Africa, especially women, regularly eat clayey soil -- this habit is known as geophagy. A previous study conducted at MedUni Vienna has already shown that it is a form of craving. Now researchers from the Center for Public Health and the Institute of Medical Genetics at MedUni Vienna have shown that this practice can also be detrimental to health: pregnant women who consume particular types of soil display higher levels of lead contamination -- as do their babies. That is the finding of a study that was produced for the dissertations of two students (Rosina Glaunach and Coloman Deweis) of MedUni Vienna and that has now been published in Environmental Research. The study involved examining mother/baby pairs in the Democratic Republic of Congo, who ate/eat clayey soil from two different regions. Blood samples taken from the mother or from the baby's umbilical cord after birth showed significantly higher lead concentrations than those found in newborn babies in Austria, for example: "We found an average lead concentration of 60 µg of lead per litre of blood in newborn babies in the Democratic Republic of Congo. By way of comparison, the lead concentration in newborns in Austria is much lower: on average we only find 13 µg of lead per litre," explain lead investigators Ruth Kutalek und Claudia Gundacker. "And it is probable that there is a direct correlation with geophagy. Consumption should definitely be reduced." The maximum limit is 155 µg. Lead concentrations in the blood are currently being re-evaluated on an international level. Says Gundacker: "The US health authority regards concentrations in excess of 50 µg/l as being so alarming that it recommends targeted public health measures to reduce these levels." The researchers' aim is now to conduct a larger study to determine more precisely which types of soil and what quantities contribute to lead contamination. This should enable us to give more specific advice to pregnant women. In this way it might be possible in future to offer food substitutes under medical supervision -- these can range from "healthier" soils through to food supplements with a high iron content but also include a general soil "diet." Geophagy is a form of substance craving, just like a craving for chocolate or as a type of "reward." Says Kutalek: "These people often eat clay as a snack between meals and report that they could not do without it." However, the reason behind it could be quite different -- and also quite multi-layered. Soil contains clay, which binds toxins, in the same way as charcoal tablets combat diarrhea. This clay could influence the pH of the stomach acid and help to combat heartburn -- many women in Africa eat a diet consisting mainly of maize, cassava and pulses. However, migrants from Africa who have come to Europe and people in Asia are in the habit of eating soil. It is sold in exotic supermarkets.

Writzl K.,Institute of Medical Genetics
American Journal of Medical Genetics, Part A | Year: 2013

The chromosome 6p21.3 microdeletion phenotype was recently identified through array comparative genomic hybridization. The main features are developmental delay with severe speech impairment, seizures, and behavioral abnormalities. Three patients have been reported with deletion sizes ranging from 100 to 800kb. We report on a 9-year-old boy with an apparently de novo, 50kb deletion, and global developmental delay, severe speech impairment, and generalized epilepsy well-controlled by medication. There were four genes identified in this deletion, of which SYNGAP1 is considered to be responsible for speech impairment and epilepsy. We compared the clinical features of this patient with previously reported patients with 6p21.3 and patients with SYNGAP1 mutations. © 2013 Wiley Periodicals, Inc.

Pierce S.B.,University of Washington | Gersak K.,University of Ljubljana | Michaelson-Cohen R.,Institute of Medical Genetics | Walsh T.,University of Washington | And 5 more authors.
American Journal of Human Genetics | Year: 2013

The genetic causes of premature ovarian failure (POF) are highly heterogeneous, and causative mutations have been identified in more than ten genes so far. In two families affected by POF accompanied by hearing loss (together, these symptoms compose Perrault syndrome), exome sequencing revealed mutations in LARS2, encoding mitochondrial leucyl-tRNA synthetase: homozygous c.1565C>A (p.Thr522Asn) in a consanguineous Palestinian family and compound heterozygous c.1077delT and c.1886C>T (p.Thr629Met) in a nonconsanguineous Slovenian family. LARS2 c.1077delT leads to a frameshift at codon 360 of the 901 residue protein. LARS2 p.Thr522Asn occurs in the LARS2 catalytic domain at a site conserved from bacteria through mammals. LARS2 p.Thr629Met occurs in the LARS2 leucine-specific domain, which is adjacent to a catalytic loop critical in all species but for which primary sequence is not well conserved. A recently developed method of detecting remote homologies revealed threonine at this site in consensus sequences derived from multiple-species alignments seeded by human and E. coli residues at this region. Yeast complementation indicated that LARS2 c.1077delT is nonfunctional and that LARS2 p.Thr522Asn is partially functional. LARS2 p.Thr629Met was functional in this assay but might be insufficient as a heterozygote with the fully nonfunctional LARS2 c.1077delT allele. A known C. elegans strain with the protein-truncating alteration LARS-2 p.Trp247Ter was confirmed to be sterile. After HARS2, LARS2 is the second gene encoding mitochondrial tRNA synthetase to be found to harbor mutations leading to Perrault syndrome, further supporting a critical role for mitochondria in the maintenance of ovarian function and hearing. © 2013 The American Society of Human Genetics.

News Article | November 4, 2015

Fifteen years ago, it was a landmark achievement. Ten years ago, it was an intriguing but highly expensive research tool. Now, falling costs, soaring accuracy and a steadily expanding base of scientific knowledge have brought genome sequencing to the cusp of routine clinical care. A growing number of institutions are conducting genome-wide 'dragnet' searches to identify the mutations responsible for rare diseases. “The rate at which we're finding causative variants in those cases is going up,” says Russ Altman, a bioinformatician at Stanford School of Medicine in California. “At some centres, it's up to 50% of cases.” Genomic variants can also reveal 'driver' mutations that might reveal a tumour's therapeutic vulnerabilities, or provide clues to whether a specific individual may or may not respond to a drug — the drug's 'pharmacogenetic' properties. The US$1,000 genome, initially conceived as a price point at which sequencing could become a component of personalized medicine, has arrived. “Our capacity for data generation relative to price has increased in a way that is almost unprecedented in science — roughly six orders of magnitude in the past seven or eight years,” says Paul Flicek, a specialist in computational genomics at the European Molecular Biology Laboratory's European Bioinformatics Institute in Cambridge, UK. The HiSeq X Ten system developed by Illumina of San Diego, California, can sequence more than 18,000 human genomes per year, for example. The biomedical research community is diving in whole-heartedly, with population-scale programmes that are intended to explore the clinical power of the genome. In 2014 the United Kingdom launched the 100,000 Genomes Project, and both the United States (under the Precision Medicine Initiative) and China (in a programme to be run by BGI of Shenzhen) have unveiled plans to analyse genomic data from one million individuals. Many other programmes are under way that, although more regional in focus, are still 'big data' operations. A partnership between Geisinger Health System, based in Danville, Pennsylvania, and biotech firm Regeneron Pharmaceuticals of Tarrytown, New York, for instance, aims to generate sequence data for more than 250,000 people. Meanwhile, a growing number of hospitals and service providers worldwide are sequencing the genomes of people with cancers or rare hereditary disorders (see 'DNA sequencing soars'). Some researchers worry that the flood of data could overwhelm the computational pipelines needed for analysis and generate unprecedented demand for storage — one article estimated that the output from genomics may soon dwarf data heavyweights such as YouTube. Many also worry that today's big data lacks the richness to provide clinical value. “I don't know if a million genomes is the right number, but clearly we need more than we've got,” says Marc Williams, director of the Geisinger Genomic Medicine Institute. Clinical genomics today is largely focused on identifying single-nucleotide variants — individual 'typos' in the genomic code that can disrupt gene function. And rather than looking at the full genome, many centres focus instead on the exome — the subset of sequences containing protein-coding genes. This reduces the amount of data being analysed nearly 100-fold, but the average exome still contains more than 13,000 single-nucleotide variants. Roughly 2% of these are predicted to affect the composition of the resulting protein, and finding the culprit for a given disease is a daunting challenge. For decades, biomedical researchers have dutifully deposited their discoveries of single-nucleotide variants in public resources such as the Human Gene Mutation Database, run by the Institute of Medical Genetics at Cardiff University, UK, or dbSNP, maintained by the US National Center for Biotechnology Information. However, the effects of these mutations were often determined from cell culture or animal models, or even theoretical predictions, providing insufficient guidance for clinical diagnostic tools. “In many cases, associations were made with relatively low levels of evidence,” says Williams. The situation is even more complicated for structural variants, such as duplicated or missing chunks of genome sequence, which are far more difficult to detect with existing sequencing technologies than single-nucleotide variants. At the whole-genome scale, each person has millions of variants. Many of these are in sequences that do not encode proteins but instead regulate gene activity, so they can still contribute to disease. However, the extent and function of these regulatory regions are poorly defined. Although capturing all this variability is desirable, it may not offer the best short-term returns for clinical sequencing. “You're shooting yourself in the foot if you're collecting data you don't know how to interpret,” says Altman. Efforts are now under way to rectify this problem. The Clinical Genome Resource, which was set up by the US National Human Genome Research Institute, is a database of disease-related variants, and contains information that could guide medical responses to these variants as well as the evidence supporting those associations. Genomics England, which runs the 100,000 Genomes Project, aims to bolster progress in this area by establishing 'clinical interpretation partnerships': doctors and researchers will collaborate to establish robust models of diseases that can potentially be mapped to specific genetic alterations. However, quantity is as important as quality. Mutations that offer a strong detrimental effect bring an evolutionary disadvantage, so they tend to be exceedingly rare and require large sample sizes to detect. Establishing statistically meaningful disease associations for variants with weak effects also needs large numbers of people. In Iceland, deCODE Genetics has demonstrated the power of population-scale genomics, combining extensive genealogy and medical-history records with genome data from 150,000 people (including 15,000 whole-genome sequences). These findings have allowed deCODE to extrapolate the population-wide distribution of known genetic risk factors, including gene variants linked to breast cancer, diabetes and Alzheimer's disease. They have also enabled studies in humans that normally require the creation of genetically modified animals. “We have established that there are about 10,000 Icelanders who have loss-of-function mutations in both copies of about 1,500 different genes,” says Kári Stefánsson, the company's chief executive. “We're putting significant effort into figuring out what impact the knockout of these genes has on individuals.” This work was helped by the homogeneous nature of the Icelandic population, but other projects require a broadly representative spectrum of donors. Efforts such as the international 1000 Genomes Project have catalogued some of the world's genetic diversity, but most data are heavily skewed towards Caucasian populations, making them less useful for clinical discovery. “Because they come from the genetic mother ship, so to speak, people of African ancestry carry a lot more genetic variants than non-Africans,” says Isaac Kohane, a bioinformatician at Harvard Medical School in Boston, Massachusetts. “Variants that seem unusual in Caucasians might be common in Africans, and may not actually cause disease.” Part of the problem stems from the reference genome — the yardstick sequence by which scientists identify apparent abnormalities, developed by the multinational Genome Reference Consortium. The first version was cobbled together from a few random donors of undefined ethnicity, but the latest iteration, known as GRCh38, incorporates more information about human genomic diversity. Harvesting genomes or even exomes at the population scale produces a vast amount of data, perhaps up to 40 petabytes (40 million gigabytes) each year. Nevertheless, raw storage is not the primary computational concern. “Genomicists are a tiny fraction of the people who need bigger hard drives,” says Flicek. “I don't think storage is a significant problem.” A greater concern is the amount of variant data being analysed from each individual. “The computation scales linearly with respect to the number of people,” says Marylyn Ritchie, a genomics researcher at Pennsylvania State University in State College. “But as you add more variables, it becomes exponential as you start to look at different combinations.” This becomes particularly problematic if there are additional data related to clinical symptoms or gene expression. Processing data of this magnitude from thousands of people can paralyse tools for statistical analysis that might work adequately in a small laboratory study. Scaling up requires improvisation, but there is no need to start from scratch. “Fields like meteorology, finance and astronomy have been integrating different types of data for a long time,” says Ritchie. “I've been to meetings where I talk to people from Google and Facebook, and our 'big data' is nothing like their big data. We should talk to them, figure out how they've done it and adopt it into our field.” Unfortunately, many talented programmers with the skills to wrangle big data sets are lured away by Silicon Valley. Philip Bourne, associate director for data science at the US National Institutes of Health (NIH), believes that this is partly due to a lack of recognition and advancement within a publication-driven system of scientific credit that leaves software creators and data managers out in the cold. “Some of these people truly want to be scholars, but they can't get the stature of faculty — that's just not right,” says Bourne. Processing power is another limiting factor. “This is not a desktop game — the real practitioners are proficient in massively parallel computation with hundreds if not thousands of CPUs, each with large memory,” says Kohane. Many groups that analyse massive amounts of sequence data are moving to 'cloud'-based architectures, in which the data are deposited within a large pool of computational resources and can then be analysed with whatever processing power is required. “There's been a gradual evolution towards this idea that you bring your algorithms to the data,” says Tim Hubbard, head of bioinformatics at Genomics England. For Genomics England, this architecture is contained in a secure government facility, with strict control over external access. Other research groups are turning to commercial cloud systems, such as those provided by Amazon or Google. In principle, cloud-based hosting can encourage sharing and collaboration on data sets. But regulations on patient consent and privacy rights surrounding highly sensitive clinical information pose tricky ethical and legal issues. In the European Union, collaboration is impeded by member states having different rules on data handling. Sharing with non-EU nations relies on cumbersome mechanisms to establish adequacy of data protection, or restrictive bilateral agreements with individual organizations. To help solve this problem, a multinational coalition, the Global Alliance for Genomics and Health, developed the Framework for Responsible Sharing of Genomic and Health-Related Data. The Framework includes guidelines on privacy and consent, as well as on accountability and legal consequences for those who break the rules. “In data-transfer agreements, you could save yourself pages and pages of rules if the institution, researcher and funder agree to follow the Framework,” says Bartha Knoppers, a bioethicist at McGill University in Montreal, Canada, who chairs the Alliance's regulatory and ethics working group. The Framework also calls for 'safe havens' that allow the research community to analyse centralized banks of genomic data that have been identity-masked but not fully 'de-identified', so they remain useful. “We want to link it to clinical data and to medical records, because we're never going to get to precision medicine otherwise, so we're going to have to use coded data,” explains Knoppers. Integrating genomics into electronic health records is becoming increasingly important for many European nations. “Our objective is to put this into the standard National Health Service,” says Hubbard. The UK 100,000 Genomes Project may be the furthest along at the moment, but other countries are following. Belgium recently announced an initiative to explore medical genomics, for example. All these nations benefit from having centralized, government-run health-care systems. In the United States, the situation is more fragmented, with different providers relying on distinct health-record systems, supplied by different vendors, that are generally not designed to handle complex genomic data. The NIH launched the Electronic Medical Records and Genomics (eMERGE) Network in 2007 to define best practices. The immediate goal of genomically enriched health records is to explain the implications of gene variants to physicians, and one of its earliest implementations is pharmacogenetics. The Clinical Pharmacogenetics Implementation Consortium has translated known drug–gene interactions reported in PharmGKB (a database run by Altman and his colleagues) for clinical use. For example, people with certain variants may respond poorly to particular anticoagulants, leading to increased risk of heart attack. “The issue there is, how do you take a practitioner who has 12 minutes per patient and about 45 seconds of time allocated for prescribing drugs, and influence their practice in a meaningful way?” says Altman. As long as deciding how to adapt care to genetic findings remains a job for humans, this process will remain time- and labour-intensive. Nevertheless, combining genotype and phenotype information is proving fruitful from a research perspective. Most clinically relevant gene variants were identified through genome-wide association studies, in which large populations of people with a given disease were examined to identify closely associated genetic signatures. Researchers can now work backwards from health records to determine what clinical manifestations are prevalent among individuals with a given genetic variant. And the genome is only part of the story — other '-omes' may also be useful barometers of health. In July, Jun Wang stepped down as chief executive of BGI to start up an organization to analyse BGI's planned million-genome cohort alongside equivalent data sets from the proteome, transcriptome and metabolome. “I will be initiating a new institution to focus on using artificial intelligence to explore this kind of big data,” he says. As researchers strive to integrate data from health records and clinical trials with genomic and other physiological data, patients are starting to contribute. “When we're focused on things like behaviour, nutrition, exercise, smoking and alcohol, you can't get better data than what patients report,” says Ritchie. Wearable devices, such as smartphones and FitBits, are collecting data on exercise and heart rate, and the volume of such data is soaring (see page S12) as it can be gathered with minimal effort on the wearer's part. Each patient may become a big-data producer. “The data we generate at home or in the wild will vastly exceed what we accumulate in clinical care,” says Kohane. “We're trying to create these big collages of different data modalities — from the genomic to the environmental to the clinical — and link them back to the patient.” As these developments materialize, they could create computational crunches that will make today's 'big data' struggles seem like pocket-calculator problems. And as scientists find ways to crunch the data, patients will be the ultimate winners.

Lattante S.,University Pierre and Marie Curie | Lattante S.,French National Center for Scientific Research | Lattante S.,Institute of Medical Genetics | Ciura S.,University Pierre and Marie Curie | And 2 more authors.
Trends in Genetics | Year: 2015

Several genetic causes have been recently described for neurological diseases, increasing our knowledge of the common pathological mechanisms involved in these disorders. Mutation analysis has shown common causative factors for two major neurodegenerative disorders, ALS and FTD. Shared pathological and genetic markers as well as common neurological signs between these diseases have given rise to the notion of an ALS/FTD spectrum. This overlap among genetic factors causing ALS/FTD and the coincidence of mutated alleles (including causative, risk and modifier variants) have given rise to the notion of an oligogenic model of disease. In this review we summarize major advances in the elucidation of novel genetic factors in these diseases which have led to a better understanding of the common pathogenic factors leading to neurodegeneration. © 2015 Elsevier Ltd.

Belostotsky R.,Shaare Zedek Medical Center | Ben-Shalom E.,Shaare Zedek Medical Center | Ben-Shalom E.,Hebrew University of Jerusalem | Rinat C.,Shaare Zedek Medical Center | And 11 more authors.
American Journal of Human Genetics | Year: 2011

An uncharacterized multisystemic mitochondrial cytopathy was diagnosed in two infants from consanguineous Palestinian kindred living in a single village. The most significant clinical findings were tubulopathy (hyperuricemia, metabolic alkalosis), pulmonary hypertension, and progressive renal failure in infancy (HUPRA syndrome). Analysis of the consanguineous pedigree suggested that the causative mutation is in the nuclear DNA. By using genome-wide SNP homozygosity analysis, we identified a homozygous identity-by-descent region on chromosome 19 and detected the pathogenic mutation c.1169A>G (p.Asp390Gly) in SARS2, encoding the mitochondrial seryl-tRNA synthetase. The same homozygous mutation was later identified in a third infant with HUPRA syndrome. The carrier rate of this mutation among inhabitants of this Palestinian isolate was found to be 1:15. The mature enzyme catalyzes the ligation of serine to two mitochondrial tRNA isoacceptors: tRNA Ser AGY and tRNA Ser UCN. Analysis of amino acylation of the two target tRNAs, extracted from immortalized peripheral lymphocytes derived from two patients, revealed that the p.Asp390Gly mutation significantly impacts on the acylation of tRNA Ser AGY but probably not that of tRNA Ser UCN. Marked decrease in the expression of the nonacylated transcript and the complete absence of the acylated tRNA Ser AGY suggest that this mutation leads to significant loss of function and that the uncharged transcripts undergo degradation. © 2011 The American Society of Human Genetics. All rights reserved.

Hoffmann K.,Institute of Medical Genetics | Heller R.,University of Cologne
Best Practice and Research: Clinical Endocrinology and Metabolism | Year: 2011

Normally, one inherits one chromosome of each pair from one parent and the second chromosome from the other parent. Uniparental disomy (UPD) describes the inheritance of both homologues of a chromosome pair from the same parent. The biological basis of UPD syndromes is disturbed genomic imprinting. The consequences of UPD depend on the specific chromosome/segment involved and its parental origin. Phenotypes range from unapparent to unmasking of an autosomal-recessive disease to presentation as a syndromic imprinting disorder. Whilst paternal UPD(7) is clinically unapparent, maternal UPD(7) is one of several causes of Silver-Russell syndrome. Presentation of paternal UPD(14) ("Kagami syndrome") is a thoracic dysplasia syndrome with mental retardation and limited survival. Findings in maternal UPD(14) ("Temple") syndrome show an age-dependent overlap with the well-known maternal UPD(15) (Prader-Willi) syndrome and are dominated by initial failure to thrive followed by obesity, learning difficulties and precocious puberty. Diagnostic strategies to tackle the genetic heterogeneity of UPD(7) and UPD(14) syndromes will be explained. Management issues in UPD(7) and UPD(14) patients will be discussed, and finally areas requiring further research will be outlined. © 2010 Elsevier Ltd. All rights reserved.

Pereza N.,University of Rijeka | Ostojic S.,University of Rijeka | Volk M.,Institute of Medical Genetics | Kapovic M.,University of Rijeka | Peterlin B.,Institute of Medical Genetics
Reproductive BioMedicine Online | Year: 2012

Idiopathic recurrent spontaneous abortion (IRSA) has been associated with abnormalities in the remodelling of endometrial extracellular matrix, as well as aberrant matrix metalloproteinase (MMP) gene expression in endometrium of IRSA women and chorionic villi of IRSA concepti. This study investigated the association of five functional MMP gene promoter polymorphisms (MMP1 -1607 1G/2G, MMP2 -735 C/T, MMP2 -1306 C/T, MMP3 -1612 5A/6A and MMP9 -1562 C/T) with IRSA. A total of 149 couples with at least three consecutive IRSA and 149 fertile couples were included in a case-control study. Genotype analysis was performed using PCR restriction fragment length polymorphism. Statistically significant differences were found in distributions of MMP2 -735 CT (chi-squared 10.21, P = 0.006; OR 2.15, 95% CI 1.34-3.45, P = 0.001), and MMP9 -1562 CC (chi-squared 9.06, P = 0.010; OR 2.21, 95% CI 1.30-3.80, P = 0.004) between IRSA women and controls. Combined analysis of MMP gene polymorphisms did not increase their predictive value. There were no statistically significant differences in genotype and allele frequencies of any polymorphism between IRSA men and controls. MMP2 -735 C/T and MMP9 -1562 C/T functional gene polymorphisms might be associated with an increased risk of IRSA in women. Considering the insufficient knowledge on genetic contribution to pregnancy loss, studies on genetic causes of idiopathic recurrent spontaneous abortion (IRSA) are of great importance. Development of a histologically and functionally normal endometrium is critical for subsequent endometrial decidualization, receptivity and implantation. The proper communication and interaction between maternal decidual cells and the embryo is essential for the establishment of a functional fetal-maternal interface. IRSA has been associated with abnormalities in the remodelling of endometrial extracellular matrix, as well as aberrant matrix metalloproteinase (MMP) gene expression in endometrium of IRSA women and chorionic villi of IRSA concepti. The aim of this study was to investigate the association of five functional MMP gene promoter polymorphisms with IRSA. A total of 149 couples with at least three consecutive IRSA and 149 fertile couples were included in a case-control study. Genotype analysis was performed using polymerase chain reaction and restriction fragment length polymorphism. Statistically significant differences were found in distribution of MMP2 -735 CT and MMP9 -1562 CC genotypes between IRSA and control women. Combined analysis of MMP gene polymorphisms did not increase their predictive value. There were no statistically significant differences in distribution of genotype and allele frequencies of any polymorphism between IRSA men and controls. Our results demonstrate that MMP2 -735 C/T and MMP9 -1562 C/T functional gene polymorphisms might be associated with an increased risk of IRSA in women. © 2012, Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Michelson M.,Institute of Medical Genetics
American journal of medical genetics. Part A | Year: 2012

Interstitial deletions of the long arm of chromosome 6 are rare. Clinically, this is a recognizable microdeletion syndrome associated with intellectual disability (ID), acquired microcephaly, typical dysmorphic features, structural anomalies of the brain, and nonspecific multiple organ anomalies. Most of the reported cases have cytogenetically visible interstitial deletions or subtelomeric microdeletions. We report on a boy with global developmental delay, distinct dysmorphic features, dysgenesis of the corpus callosum, limb anomalies, and genital hypoplasia who has a small interstitial deletion of the long arm of chromosome 6 detected by comparative genomic hybridization (CGH). The deleted region spans around 1 Mb of DNA and contains only two coding genes, ARID1B and ZDHHC14. To the best of our knowledge, this case represents the typical phenotype with the smallest deletion reported so far. We discuss the possible role of these genes in the phenotypic manifestations. Copyright © 2012 Wiley Periodicals, Inc.

Rauch A.,Institute of Medical Genetics
Best Practice and Research: Clinical Endocrinology and Metabolism | Year: 2011

Microcephalic or Majewski's osteodysplastic primordial dwarfism type II (MOPD II) represents the most common type of primordial dwarfism. Adult height is typically about one meter and short stature is becoming mildly disproportionate over time with mild skeletal anomalies. Mental development is usually borderline or within the low normal range but cerebrovascular events that are common in childhood can result in significant cognitive impairment and cerebral palsy. Despite cerebrovascular insults, cardiomyopathy and early onset type 2 diabetes contribute to early mortality and morbidity. Common minor clinical features are truncal obesity, high pitched voice, microdontia and pigmentary changes. MOPD II is caused by autosomal recessive loss of function mutations in the PCNT gene encoding for a key centrosomal protein. There is clinical overlap with the so called Seckel syndrome, a heterogeneous group of entities with at least four different gene loci known to date. © 2010 Elsevier Ltd. All rights reserved.

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