Hereditary hypophosphatemic rickets with hypercalciuria (HHRH) is a rare disorder of autosomal recessive inheritance that was first described in a large consanguineous Bedouin kindred. HHRH is characterized by the presence of hypophosphatemia secondary to renal phosphate wasting, radiographic and/or histological evidence of rickets, limb deformities, muscle weakness, and bone pain. HHRH is distinct from other forms of hypophosphatemic rickets in that affected individuals present with hypercalciuria due to increased serum 1,25-dihydroxyvitamin D levels and increased intestinal calcium absorption. We performed a genomewide linkage scan combined with homozygosity mapping, using genomic DNA from a large consanguineous Bedouin kindred that included 10 patients who received the diagnosis of HHRH. The disease mapped to a 1.6-Mbp region on chromosome 9q34, which contains SLC34A3, the gene encoding the renal sodium-phosphate cotransporter NaP(i)-IIc. Nucleotide sequence analysis revealed a homozygous single-nucleotide deletion (c.228delC) in this candidate gene in all individuals affected by HHRH. This mutation is predicted to truncate the NaP(i)-IIc protein in the first membrane-spanning domain and thus likely results in a complete loss of function of this protein in individuals homozygous for c.228delC. In addition, compound heterozygous missense and deletion mutations were found in three additional unrelated HHRH kindreds, which supports the conclusion that this disease is caused by SLC34A3 mutations affecting both alleles. Individuals of the investigated kindreds who were heterozygous for a SLC34A3 mutation frequently showed hypercalciuria, often in association with mild hypophosphatemia and/or elevations in 1,25-dihydroxyvitamin D levels. We conclude that NaP(i)-IIc has a key role in the regulation of phosphate homeostasis.

Renal disease variability in autosomal dominant polycystic kidney disease (ADPKD) is strongly influenced by the gene locus (PKD1 versus PKD2). Recent studies identified nontruncating PKD1 mutations in approximately 30% of patients who underwent comprehensive mutation screening, but the clinical significance of these mutations is not well defined. We examined the genotype-renal function correlation in a prospective cohort of 220 unrelated ADPKD families ascertained through probands with serum creatinine #1.4 mg/dl at recruitment. We screened these families for PKD1 and PKD2 mutations and reviewed the clinical outcomes of the probands and affected family members. Height-adjusted total kidney volume (htTKV) was obtained in 161 affected subjects. Multivariate Cox proportional hazard modeling for renal and patient survival was performed in 707 affected probands and family members. Overall, we identified pathogenic mutations in 84.5% of our families, in which the prevalence of PKD1 truncating, PKD1 in-frame insertion/deletion, PKD1 nontruncating, and PKD2 mutations was 38.3%, 4.3%, 27.1%, and 30.3%, respectively. Compared with patients with PKD1 truncating mutations, patients with PKD1 in-frame insertion/deletion, PKD1 nontruncating, or PKD2 mutations have smaller htTKV and reduced risks (hazard ratio Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disease worldwide, responsible for 5%-10% of ESRD. 1,2 Mutations in two genes (PKD1 and PKD2) account for most patients with ADPKD. 2,3 Previous studies of European families ascertained through probands enriched with renal failure reported that approximately 85% and approximately 15% of ADPKD families were linked to the PKD1 and PKD2 loci, respectively. 3 However, a higher prevalence of PKD2 of 26% has been recently reported in a population-based study. 4 Disease progression of ADPKD is highly variable, in part because of a strong gene locus effect. [5][6][7][8] Adjusted for age, patients with PKD1 have larger kidneys and earlier onset of ESRD than patients with PKD2 (mean age at ESRD, 53.4 versus 72.7 years old, respectively). 5,6,8 Additionally, significant intrafamilial renal disease variability in ADPKD suggests a modifier effect. [9][10][11] [

Mucopolysaccharidosis IIIC (MPS IIIC, or Sanfilippo C syndrome) is a lysosomal storage disorder caused by the inherited deficiency of the lysosomal membrane enzyme acetyl-coenzyme A: alpha -glucosaminide N-acetyltransferase (N-acetyltransferase), which leads to impaired degradation of heparan sulfate. We report the narrowing of the candidate region to a 2.6-cM interval between D8S1051 and D8S1831 and the identification of the transmembrane protein 76 gene (TMEM76), which encodes a 73-kDa protein with predicted multiple transmembrane domains and glycosylation sites, as the gene that causes MPS IIIC when it is mutated. Four nonsense mutations, 3 frameshift mutations due to deletions or a duplication, 6 splice-site mutations, and 14 missense mutations were identified among 30 probands with MPS IIIC. Functional expression of human TMEM76 and the mouse ortholog demonstrates that it is the gene that encodes the lysosomal N-acetyltransferase and suggests that this enzyme belongs to a new structural class of proteins that transport the activated acetyl residues across the cell membrane.

Due to rapid technological advances, various types of genomic and proteomic data with different sizes, formats, and structures have become available. Among them are gene expression, single nucleotide polymorphism, copy number variation, and protein-protein/gene-gene interactions. Each of these distinct data types provides a different, partly independent and complementary, view of the whole genome. However, understanding functions of genes, proteins, and other aspects of the genome requires more information than provided by each of the datasets. Integrating data from different sources is, therefore, an important part of current research in genomics and proteomics. Data integration also plays important roles in combining clinical, environmental, and demographic data with high-throughput genomic data. Nevertheless, the concept of data integration is not well defined in the literature and it may mean different things to different researchers. In this paper, we first propose a conceptual framework for integrating genetic, genomic, and proteomic data. The framework captures fundamental aspects of data integration and is developed taking the key steps in genetic, genomic, and proteomic data fusion. Secondly, we provide a review of some of the most commonly used current methods and approaches for combining genomic data with focus on the statistical aspects.

Shwachman-Diamond syndrome (SDS) is an autosomal recessive disorder characterized by exocrine pancreatic insufficiency and hematologic and skeletal abnormalities. A genomewide scan of families with SDS was terminated at approximately 50% completion, with the identification of chromosome 7 markers that showed linkage with the disease. Finer mapping revealed significant linkage across a broad interval that included the centromere. The maximum two-point LOD score was 8.7, with D7S473, at a recombination fraction of 0. The maximum multipoint LOD score was 10, in the interval between D7S499 and D7S482 (5.4 cM on the female map and 0 cM on the male map), a region delimited by recombinant events detected in affected children. Evidence from all 15 of the multiplex families analyzed provided support for the linkage, consistent with a single locus for SDS. However, the presence of several different mutations is suggested by the heterogeneity of disease-associated haplotypes in the candidate region.