Detection of nonrandom association of alleles from the distribution of the number of heterozygous loci in a sample.

The distribution of the number of heterozygous loci in two randomly chosen gametes or in a random diploid zygote provides information regarding the nonrandom association of alleles among different genetic loci. Two alternative statistics may be employed for detection of nonrandom association of genes of different loci when observations are made on these distributions: observed variance of the number of heterozygous loci (s2k) and a goodness-of-fit criterion (X2) to contrast the observed distribution with that expected under the hypothesis of random association of genes. It is shown, by simulation, that s2k is statistically more efficient than X2 to detect a given extent of nonrandom association. Asymptotic normality of s2k is justified, and X2 is shown to follow a chi-square (chi 2) distribution with partial loss of degrees of freedom arising because of estimation of parameters from the marginal gene frequency data. Whenever direct evaluations of linkage disequilibrium values are possible, tests based on maximum likelihood estimators of linkage disequilibria require a smaller sample size (number of zygotes or gametes) to detect a given level of nonrandom association in comparison with that required if such tests are conducted on the basis of s2k. Summarization of multilocus genotype (or haplotype) data, into the different number of heterozygous loci classes, thus, amounts to appreciable loss of information.

Identification of the Causative Bacteria in Musculoskeletal Infections Using 16s rDNA - Denaturing Gradient Gel Electrophoresis Analysis

Musculoskeletal infections are infections of the bone and surrounding tissues. They are currently diagnosed based on culture analysis, which is the gold standard for pathogen identification. However, these clinical laboratory methods are frequently inadequate for the identification of the causative agents, because a large percentage (25-50%) of confirmed musculoskeletal infections are false negatives in which no pathogen is identified in culture. My data supports these results. The goal of this project was to use PCR amplification of a portion of the 16S rRNA gene to test an alternative approach for the identification of these pathogens and to assess the diversity of the bacteria involved. The advantages of this alternative method are that it should increase sample sensitivity and the speed of detection. In addition, bacteria that are non-culturable or in low abundance can be detected using this molecular technique. However, a complication of this approach is that the majority of musculoskeletal infections are polymicrobial, which prohibits direct identification from the infected tissue by DNA sequencing of the initial 16S rDNA amplification products. One way to solve this problem is to use denaturing gradient gel electrophoresis (DGGE) to separate the PCR products before DNA sequencing. Denaturing gradient gel electrophoresis (DGGE) separates DNA molecules based on their melting point, which is determined by their DNA sequence. This analytical technique allows a mixture of PCR products of the same length that electrophoreses through agarose gels as one band, to be separated into different bands and then used for DNA sequence analysis. In this way, the DGGE allows for the identification of individual bacterial species in polymicrobial-infected tissue, which is critical for improving clinical outcomes. By combining the 16S rDNA amplification and the DGGE techniques together, an alternative approach for identification has been used. The 16S rRNA gene PCR-DGGE method includes several critical steps: DNA extraction from tissue biopsies, amplification of the bacterial DNA, PCR product separation by DGGE, amplification of the gel-extracted DNA, and DNA sequencing and analysis. Each step of the method was optimized to increase its sensitivity and for rapid detection of the bacteria present in human tissue samples. The limit of detection for the DNA extraction from tissue was at least 20 Staphylococcus aureus cells and the limit of detection for PCR was at least 0.05 pg of template DNA. The conditions for DGGE electrophoreses were optimized by using a double gradient of acrylamide (6 – 10%) and denaturant (30-70%), which increased the separation between distinct PCR products. The use of GelRed (Biotium) improved the DNA visualization in the DGGE gel. To recover the DNA from the DGGE gels the gel slices were excised, shredded in a bead beater, and the DNA was allowed to diffuse into sterile water overnight. The use of primers containing specific linkers allowed the entire amplified PCR product to be sequenced and then analyzed. The optimized 16S rRNA gene PCR-DGGE method was used to analyze 50 tissue biopsy samples chosen randomly from our collection. The results were compared to those of the Memorial Hermann Hospital Clinical Microbiology Laboratory for the same samples. The molecular method was congruent for 10 of the 17 (59%) culture negative tissue samples. In 7 of the 17 (41%) culture negative the molecular method identified a bacterium. The molecular method was congruent with the culture identification for 7 of the 33 (21%) positive cultured tissue samples. However, in 8 of the 33 (24%) the molecular method identified more organisms. In 13 of the 15 (87%) polymicrobial cultured tissue samples the molecular method identified at least one organism that was also identified by culture techniques. Overall, the DGGE analysis of 16S rDNA is an effective method to identify bacteria not identified by culture analysis.

Evaluation of androgenicity, abdominal adiposity, blood pressure and types of ovulatory patterns in a sample of women with menstrual irregularities

Objective: To determine the prevalence of and the relationships between the degree and source of hyperandrogenemia, ovulatory patterns and cardiovascular disease risk indicators (blood pressure, indices or amount of obesity and fat distribution) in women with menstrual irregularities seen at endocrinologists' clinic. Design: A cross-sectional study design. Participants: A sample of 159 women with menstrual irregularities, aged 15-44, seen at endocrinologists' clinic. Main Outcome Measures: androgen levels, body mass index (BMI), waist-hip ratio (WHR), systolic and diastolic blood pressure (SBP & DBP), source of androgens, ovulatory activity. Results: The prevalence of hyperandrogenemia was 54.7% in this study sample. As expected, women with acne or hirsutism had an odds ratio 12.5 (95%CI = 5.2-25.5) times and 36 (95%CI = 12.9-99.5) times more likely to have hyperandrogenemia than those without acne or hirsutism. The main findings of this study were the following: Hyperandrogenemic women were more likely to have oligomenorrheic cycles (OR = 3.8, 95%CI = 1.5-9.9), anovulatory cycles (OR = 6.6, 95%CI = 2.8-15.4), general obesity (BMI $\ge$ 27) (OR = 6.8, 95%CI = 2.2-27.2) and central obesity (WHR $\ge$ 127) (OR = 14.5, 95%CI = 6.1-38.7) than euandrogenemic women. Hyperandrogenemic women with non-suppressible androgens had a higher mean BMI (29.3 $\pm$ 8.9) than those with suppressible androgens (27.9 $\pm$ 7.9); the converse was true for abdominal adiposity (WHR). Hyperandrogenemic women had a 2.4 odds ratio (95%CI = 1.0-6.2) for an elevated SBP and a 2.7 odds ratio (95%CI = 0.8-8.8) for elevated DBP. When age differences were accounted for, this relationship was strengthened and further strengthened when sources of androgens were controlled. When the differences in BMI were controlled, the odds ratio for elevated SBP in hyperandrogenemic women increased to 8.8 (95%CI = 1.1-69.9). When the age, the source of androgens, the amount of obesity and the type of obesity were controlled, hyperandrogenemic women had 13.5 (95%CI = 1.1-158.9) odds ratio for elevated SBP. Conclusions: In this study population, the presence of menstrual irregularities are highly predictive for the presence of elevated androgens. Women with elevated androgens have a high risk for obesity, more specifically for central obesity. The androgenemic status is an independent predictor of blood pressure elevation. It is probable that in the general population, the presence of menstrual irregularities are predictive of hyperandrogenemia. There is a great need for a population study of the prevalence of hyperandrogenemia and for longitudinal studies in hyperandrogenemic women (adrenarche to menopause) to investigate the evolution of these relationships. ^