Common genetic variation and the control of HIV-1 in humans.

To extend the understanding of host genetic determinants of HIV-1 control, we performed a genome-wide association study in a cohort of 2,554 infected Caucasian subjects. The study was powered to detect common genetic variants explaining down to 1.3% of the variability in viral load at set point. We provide overwhelming confirmation of three associations previously reported in a genome-wide study and show further independent effects of both common and rare variants in the Major Histocompatibility Complex region (MHC). We also examined the polymorphisms reported in previous candidate gene studies and fail to support a role for any variant outside of the MHC or the chemokine receptor cluster on chromosome 3. In addition, we evaluated functional variants, copy-number polymorphisms, epistatic interactions, and biological pathways. This study thus represents a comprehensive assessment of common human genetic variation in HIV-1 control in Caucasians.

Distribution, ecology, life history, genetic variation, and risk of extinction of nonhuman primates from Costa Rica

We examined the association between geographic distribution, ecological traits, life history, genetic diversity, and risk of extinction in nonhuman primate species from Costa Rica. All of the current nonhuman primate species from Costa Rica are included in the study; spider monkeys (Ateles geoffroyi), howling monkeys (Alouatta palliata), capuchins (Cebus capucinus), and squirrel monkeys (Saimiri oerstedii). Geographic distribution was characterized accessing existing databases. Data on ecology and life history traits were obtained through a literature review. Genetic diversity was characterized using isozyme electrophoresis. Risk of extinction was assessed from the literature. We found that species differed in all these traits. Using these data, we conducted a Pearson correlation between risk of extinction and ecological and life history traits, and genetic variation, for widely distributed species. We found a negative association between risk of extinction and population birth and growth rates; indicating that slower reproducing species had a greater risk of extinction. We found a positive association between genetic variation and risk of extinction; i.e., species showing higher genetic variation had a greater risk of extinction. The relevance of these traits for conservation efforts is discussed.

Impact of Genetic Testing and Family Health History Based Risk Counseling on Behavior Change and Cognitive Precursors for Type 2 Diabetes.

Family health history (FHH) in the context of risk assessment has been shown to positively impact risk perception and behavior change. The added value of genetic risk testing is less certain. The aim of this study was to determine the impact of Type 2 Diabetes (T2D) FHH and genetic risk counseling on behavior and its cognitive precursors. Subjects were non-diabetic patients randomized to counseling that included FHH +/- T2D genetic testing. Measurements included weight, BMI, fasting glucose at baseline and 12 months and behavioral and cognitive precursor (T2D risk perception and control over disease development) surveys at baseline, 3, and 12 months. 391 subjects enrolled of which 312 completed the study. Behavioral and clinical outcomes did not differ across FHH or genetic risk but cognitive precursors did. Higher FHH risk was associated with a stronger perceived T2D risk (pKendall < 0.001) and with a perception of "serious" risk (pKendall < 0.001). Genetic risk did not influence risk perception, but was correlated with an increase in perception of "serious" risk for moderate (pKendall = 0.04) and average FHH risk subjects (pKendall = 0.01), though not for the high FHH risk group. Perceived control over T2D risk was high and not affected by FHH or genetic risk. FHH appears to have a strong impact on cognitive precursors of behavior change, suggesting it could be leveraged to enhance risk counseling, particularly when lifestyle change is desirable. Genetic risk was able to alter perceptions about the seriousness of T2D risk in those with moderate and average FHH risk, suggesting that FHH could be used to selectively identify individuals who may benefit from genetic risk testing.

Comparative analyses of seven algorithms for copy number variant identification from single nucleotide polymorphism arrays.

Determination of copy number variants (CNVs) inferred in genome wide single nucleotide polymorphism arrays has shown increasing utility in genetic variant disease associations. Several CNV detection methods are available, but differences in CNV call thresholds and characteristics exist. We evaluated the relative performance of seven methods: circular binary segmentation, CNVFinder, cnvPartition, gain and loss of DNA, Nexus algorithms, PennCNV and QuantiSNP. Tested data included real and simulated Illumina HumHap 550 data from the Singapore cohort study of the risk factors for Myopia (SCORM) and simulated data from Affymetrix 6.0 and platform-independent distributions. The normalized singleton ratio (NSR) is proposed as a metric for parameter optimization before enacting full analysis. We used 10 SCORM samples for optimizing parameter settings for each method and then evaluated method performance at optimal parameters using 100 SCORM samples. The statistical power, false positive rates, and receiver operating characteristic (ROC) curve residuals were evaluated by simulation studies. Optimal parameters, as determined by NSR and ROC curve residuals, were consistent across datasets. QuantiSNP outperformed other methods based on ROC curve residuals over most datasets. Nexus Rank and SNPRank have low specificity and high power. Nexus Rank calls oversized CNVs. PennCNV detects one of the fewest numbers of CNVs.