Influence of Familial Renal Glycosuria Due to Mutations in the SLC5A2 Gene on Changes in Glucose Tolerance over Time

Familial renal glycosuria is an inherited disorder resulting in glucose excretion in the urine despite normal blood glucose concentrations. It is most commonly due to mutations in the SLC5A2 gene coding for the glucose transporter SGLT2 in the proximal tubule. Several drugs have been introduced as means to lower glucose in patients with type 2 diabetes targeting SGLT2 resulting in renal glycosuria, but no studies have addressed the potential effects of decreased renal glucose reabsorption and chronic glycosuria on the prevention of glucose intolerance. Here we present data on a large pedigree with renal glycosuria due to two mutations (c.300-303+2del and p.A343V) in the SLC5A2 gene. The mutations, which in vitro affected glucose transport in a cell line model, and the ensuing glycosuria were not associated with better glycemic control during a follow-up period of more than 10 years. One individual, who was compound heterozygous for mutations in the SLC5A2 gene suffered from severe urogenital candida infections and postprandial hypoglycemia. In conclusion, in this family with familial glycosuria we did not find any evidence that chronic loss of glucose in the urine would protect from deterioration of the glucose tolerance over time.     

Affinity Proteomics Exploration of Melanoma Identifies Proteins in Serum with Associations to T-Stage and Recurrence

BACKGROUND: Blood-based proteomic profiling may aid and expand our understanding of diseases and their different phenotypes. The aim of the presented study was to profile serum samples from patients with malignant melanoma using affinity proteomic assays to describe proteins in the blood stream that are associated to stage or recurrence of melanoma. MATERIAL AND METHODS: Multiplexed protein analysis was conducted using antibody suspension bead arrays. A total of 232 antibodies against 132 proteins were selected from (i) a screening with 4595 antibodies and 32 serum samples from melanoma patients and controls, (ii) antibodies used for immunohistochemistry, (iii) protein targets previously related with melanoma. The analysis was performed with 149 serum samples from patients with malignant melanoma. Antibody selectivity was then assessed by Western blot, immunocapture mass spectrometry, and epitope mapping. Lastly, indicative antibodies were applied for IHC analysis of melanoma tissues. RESULTS: Serum levels of regucalcin (RGN) and syntaxin 7 (STX7) were found to be lower in patients with both recurring tumors and a high Breslow's thickness (T-stage 3/4) compared to low thickness (T-stage 1/2) without disease recurrence. Serum levels of methylenetetrahydrofolate dehydrogenase 1-like (MTHFD1L) were instead elevated in sera of T3/4 patients with recurrence. The analysis of tissue sections with S100A6 and MTHFD1L showed positive staining in a majority of patients with melanoma, and S100A6 was significantly associated to T-stage. CONCLUSIONS: Our findings provide a starting point to further study RGN, STX7, MTHFD1L and S100A6 in serum to elucidate their involvement in melanoma progression and to assess a possible contribution to support clinical indications.     

A Rapid Technic for Demonstrating mast cells in Mouse Skin

A simple rapid technic is described for demonstrating mast cells in mouse skin. The procedure requires about 60 minutes from time of specimen removal until permanent mounting. The steps comprise: (1) stretch-mounting of skin on a cardboard frame; (2) fixing and dehydrating in absolute ethanol for 15 minutes; (3) xylene washing for 10 minutes; (4) absolute ethanol washing for 10-15 minutes; (5) 3-4 minutes in a 0.1% aqueous solution of methylene blue; (6) dehydrating and differentiating in absolute ethanol; (7) clearing in xylene; (8) trimming and mounting. Cell counts may be made immediately, as well as high dry and oil immersion study of cytological detail of mast cells.     

Characterization of systemic metabolic phenotypes associated with subclinical atherosclerosis

Detailed molecular phenotyping gives insight into disease mechanisms and can individualize medical practice for improved risk assessment and treatment. We show in an epidemiological study (n = 4309) that the multi-metabolic profiles obtained by serum NMR metabonomics inherently associate with the extent of atherosclerosis already in preclinical stages. Data-driven analysis of the spectral profiles of healthy, young adults revealed three distinct metabolic phenotypes associated with high carotid intima-media thickness (IMT), a surrogate marker of cardiovascular disease. The phenotypes were characterized by varying combinations of well-known metabolic disturbances like elevated VLDL and LDL and low HDL levels. Low IMT was also associated with distinct metabolic phenotypes with lipoprotein as well as other biochemical characteristics partly opposing those found for the high IMT phenotypes. Profiles of low-molecular-weight metabolites quantified from the experimentation were also characteristic for the metabolic phenotypes and substantiate developments toward the use of multi-metabolic risk phenotypes. The methodology can be taken as a direct extension for the routine analytics used for the risk assessment of atherosclerosis; quantification of metabolites will complement and might even replace conventional lipid measurements. Serum NMR metabonomics is therefore anticipated as a rational option for comprehensive cardiovascular risk assessment.     

Metabolic diversity of progressive kidney disease in 325 patients with type 1 diabetes (the FinnDiane Study)

Type 1 diabetic patients with varying severity of kidney disease were investigated to create multimetabolite models of the disease process. Urinary albumin excretion rate was measured for 3358 patients with type 1 diabetes. Prospective records were available for 1051 patients, of whom 163 showed progression of albuminuria (8.3-year follow-up), and 162 were selected as stable controls. At baseline, serum lipids, lipoprotein subclasses, and low-molecular weight metabolites were quantified by NMR spectroscopy (325 samples). The data were analyzed by the self-organizing map. In cross-sectional analyses, patients with no complications had low serum lipids, less inflammation, and better glycemic control, whereas patients with advanced kidney disease had high serum cystatin-C and sphingomyelin. These phenotype extremes shared low unsaturated fatty acids (UFAs) and phospholipids. Prospectively, progressive albuminuria was associated with high UFAs, phospholipids, and IDL and LDL lipids. Progression at longer duration was associated with high HDL lipids, whereas earlier progression was associated with poor glycemic control, increased saturated fatty acids (SFAs), and inflammation. Diabetic kidney disease consists of diverse metabolic phenotypes: UFAs, phospholipids, IDL, and LDL may be important in the subclinical phase, high SFAs and low HDL suggest accelerated progression, and the sphingolipid pathway in advanced kidney injury deserves further research.     

Antibodies for profiling the human proteome-The Human Protein Atlas as a resource for cancer research

In this review, we present an update on the progress of the Human Protein Atlas, with an emphasis on strategies for validating immunohistochemistry-based protein expression patterns and on the possibilities to extend the map of protein expression patterns for cancer research projects. The objectives underlying the Human Protein Atlas include (i) the generation of validated antibodies toward a major isoform of all proteins encoded by the human genome, (ii) creating an information database of protein expression patterns in normal human tissues, in cells, and in cancer, and (iii) utilizing generated antibodies and protein expression data as tools to identify clinically useful biomarkers. The success of such an effort is dependent on the validity of antibodies as specific binders of intended targets in applications used to map protein expression patterns. The development of strategies to support specific target binding is crucial and remains a challenge as a large fraction of proteins encoded by the human genome is poorly characterized, including the approximately one-third of all proteins lacking evidence of existence. Conceivable methods for validation include the use of paired antibodies, i.e. two independent antibodies targeting different and nonoverlapping epitopes on the same protein as well as comparative analysis of mRNA expression patterns with corresponding proteins.     

Bias in Observational Studies of the Association between Menopausal Hormone Therapy and Breast Cancer

BackgroundDuring the period 1985-2000 the breast cancer incidence rates increased 50% in the age group invited to mammography screening in Norway and Sweden. Simultaneously, use of hormone replacement treatment therapy (HT) increased 5 times. Several influential observational studies showed that HT was associated with 50% to 100% increased risk of breast cancer and most for those using combined (estrogen plus progestin) hormone replacement therapy (CHT). In contrast, the randomized WHI trial reported that CHT increased the risk by 10% for those not having previously used hormones and 24% when including previous users in the analyses. In another randomized trial, estrogen use only was not associated with any increased risk at all. After the WHI trial was published in 2003, use of HT dropped 70% within 5 years in Norway and Sweden while breast cancer rates were essentially unchanged. After 2008, HT use has dropped further and breast cancer incidence rates have started increasing again. The study objective is to calculate and to explain potential bias in the observational study design.ConclusionsWe suggest that the mechanism causing higher hazard ratio of breast cancer (compared to the observational studies) is the time-varying effect of CHT on the breast cancer risk and selective retrospective reporting of hormone use. Other risk factors for the increase in breast cancer risk in the age group 50-69 years should be considered, for example, overdiagnosis.