PubMed Health⌕ Search

Biomedical subjects

Nathan J Markward

Publications and source records attributed to Nathan J Markward.

4 recordsLinked to original sources

Diet-genotype interactions in the development of the obese, insulin-resistant phenotype of C57BL/6J mice lacking melanocortin-3 or -4 receptors.

Loss of brain melanocortin receptors (Mc3rKO and Mc4rKO) causes increased adiposity and exacerbates diet-induced obesity (DIO). Little is known about how Mc3r or Mc4r genotype, diet, and obesity affect insulin sensitivity. Insulin resistance, assessed by insulin and glucose tolerance tests, Ser(307) phosphorylation of insulin receptor substrate 1, and activation of protein kinase B, was examined in control and DIO wild-type (WT), Mc3rKO and Mc4rKO C57BL/6J mice. Mc4rKO mice were hyperphagic and had increased metabolic efficiency (weight gain per kilojoule consumed) relative to WT; both parameters increased further on high-fat diet. Obesity of Mc3rKO was more dependent on fat intake, involving increased metabolic efficiency. Fat mass of DIO Mc3rKO and Mc4rKO was similar, although Mc4rKO gained weight more rapidly. Mc4rKO develop hepatic insulin resistance and severe hepatic steatosis with obesity, independent of diet. DIO caused further deterioration of insulin action in Mc4rKO of either sex and, in male Mc3rKO, compared with controls, associated with increased fasting insulin, severe glucose intolerance, and reduced insulin signaling in muscle and adipose tissue. DIO female Mc3rKO exhibited very modest perturbations in glucose metabolism and insulin sensitivity. Consistent with previous data suggesting impaired fat oxidation, both Mc3rKO and Mc4rKO had reduced muscle oxidative metabolism, a risk factor for weight gain and insulin resistance. Energy expenditure was, however, increased in Mc4rKO compared with Mc3rKO and controls, perhaps due to hyperphagia and metabolic costs associated with rapid growth. In summary, DIO affects insulin sensitivity more severely in Mc4rKO compared with Mc3rKO, perhaps due to a more positive energy balance.

Adipose Tissue↗

Large-scale association study identifies ICAM gene region as breast and prostate cancer susceptibility locus.

We conducted a large-scale association study to identify genes that influence nonfamilial breast cancer risk using a collection of German cases and matched controls and >25,000 single nucleotide polymorphisms located within 16,000 genes. One of the candidate loci identified was located on chromosome 19p13.2 [odds ratio (OR) = 1.5, P = 0.001]. The effect was substantially stronger in the subset of cases with reported family history of breast cancer (OR = 3.4, P = 0.001). The finding was subsequently replicated in two independent collections (combined OR = 1.4, P < 0.001) and was also associated with predisposition to prostate cancer in an independent sample set of prostate cancer cases and matched controls (OR = 1.4, P = 0.002). High-density single nucleotide polymorphism mapping showed that the extent of association spans 20 kb and includes the intercellular adhesion molecule genes ICAM1, ICAM4, and ICAM5. Although genetic variants in ICAM5 showed the strongest association with disease status, ICAM1 is expressed at highest levels in normal and tumor breast tissue. A variant in ICAM5 was also associated with disease progression and prognosis. Because ICAMs are suitable targets for antibodies and small molecules, these findings may not only provide diagnostic and prognostic markers but also new therapeutic opportunities in breast and prostate cancer.

Adult↗

Establishing mathematical laws of genomic variation.

As the biological arm of the Rasch community, genomic measurement is concerned with asserting and testing hypotheses regarding the quantitative status of genomic variables, including alleles, genotypes, gene expression levels, and phenotypes, as well as DNA, RNA, and protein sequence information. The defining goal of this scientific paradigm, in contrast to the sample-dependent model-fitting and deterministic hypothesis testing of classical statistical genetics, is the identification, validation, and maintenance of a common unit of genomic measurement that maintains its magnitude and meaning, within an allowable range of error, regardless of the laboratory technology used to generate outcomes or the particular group of individuals or organisms under investigation. Such an invariant metric, the basis of a standard genometric scale and associated system of genomic metrology, can be identified, validated, and maintained through 1) routine implementation of the Rasch family of measurement models to construct sample- and scale-free measures from different types of genomic data and 2) cross-calibration of genomic measurement instruments between and among researchers, laboratories, universities, corporations, and databases. This manuscript provides an introductory overview of the guiding principles of fundamental measurement theory and the work of Rasch, connects these concepts to well-known tenets of population genetics, and highlights the potential benefits, both theoretical and applied, associated with achieving objectivity in genomic measurement.

Animals↗

Calibrating the genome.

PURPOSE: This project demonstrates how to calibrate different samples and scales of genomic information to a common scale of genomic measurement. MATERIALS AND METHODS: 1,113 persons were genotyped at the 13 Combined DNA Index System (CODIS) short tandem repeat (STR) marker loci used by the Federal Bureau of Investigation (FBI) for human identity testing. A measurement model of form ln[(P(nik))/(1-P(nik))] = B(n)-D(i)-L(k) is used to construct person measures and locus calibrations from information contained in the CODIS database. Winsteps (Wright and Linacre, 2003) is employed to maximize initial estimates and to investigate the necessity and sufficiency of different rating classification schema. RESULTS: Model fit is satisfactory in all analyses. Study outcomes are found in Tables 1-6. CONCLUSIONS: Additive, divisible, and interchangeable measures and calibrations can be created from raw genomic information that transcend sample- and scale-dependencies associated with racial and ethnic descent, chromosomal location, and locus-specific allele expansion structures.

Alleles↗