Nuclear-Mitochondrial interactions influence susceptibility to HIV-associated neurocognitive impairment.

HIV-associated neurocognitive impairment (NCI) is a term established to capture a wide spectrum of HIV related neurocognitive deficits ranging in severity from asymptomatic to dementia. The genetic underpinnings of this complex phenotype are incompletely understood. Mitochondrial function has long been thought to play a role in neurodegeneration, along with iron metabolism and transport. In this work, we aimed to characterize the interplay of mitochondrial DNA (mtDNA) haplogroup and nuclear genetic associations to NCI phenotypes in the CHARTER cohort, encompassing 1025 individuals of European-descent, African-descent, or admixed Hispanic. We first employed a polygenic modeling approach to investigate the global effect of previous marginally associated nuclear SNPs, and to examine how the polygenic effect of these SNPs is influenced by mtDNA haplogroups. We see evidence of a significant interaction between nuclear SNPs en masse and mtDNA haplogroups within European-descent and African-descent individuals. Subsequently, we performed an analysis of each SNP by mtDNA haplogroup, and detected significant interactions between two nuclear SNPs (rs17160128 and rs12460243) and European haplogroups. These findings, which require validation in larger cohorts, indicate a potential new role for nuclear-mitochondrial DNA interactions in susceptibility to NCI and shed light onto the pathophysiology of this neurocognitive phenotype.

Cerebrospinal Fluid Ceruloplasmin, Haptoglobin, and Vascular Endothelial Growth Factor Are Associated with Neurocognitive Impairment in Adults with HIV Infection.

Dysregulated iron transport and a compromised blood-brain barrier are implicated in HIV-associated neurocognitive disorders (HAND). We quantified the levels of proteins involved in iron transport and/or angiogenesis-ceruloplasmin, haptoglobin, and vascular endothelial growth factor (VEGF)-as well as biomarkers of neuroinflammation, in cerebrospinal fluid (CSF) from 405 individuals with HIV infection and comprehensive neuropsychiatric assessments. Associations with HAND [defined by a Global Deficit Score (GDS) ≥ 0.5, GDS as a continuous measure (cGDS), or by Frascati criteria] were evaluated for the highest versus lowest tertile of each biomarker, adjusting for potential confounders. Higher CSF VEGF was associated with GDS-defined impairment [odds ratio (OR) 2.17, p = 0.006] and cGDS in unadjusted analyses and remained associated with GDS impairment after adjustment (p = 0.018). GDS impairment was also associated with higher CSF ceruloplasmin (p = 0.047) and with higher ceruloplasmin and haptoglobin in persons with minimal comorbidities (ORs 2.37 and 2.13, respectively; both p = 0.043). In persons with minimal comorbidities, higher ceruloplasmin and haptoglobin were associated with HAND by Frascati criteria (both p < 0.05), and higher ceruloplasmin predicted worse impairment (higher cGDS values, p < 0.01). In the subgroup with undetectable viral load and minimal comorbidity, CSF ceruloplasmin and haptoglobin were strongly associated with GDS impairment (ORs 5.57 and 2.96, respectively; both p < 0.01) and HAND (both p < 0.01). Concurrently measured CSF IL-6 and TNF-α were only weakly correlated to these three biomarkers. Higher CSF ceruloplasmin, haptoglobin, and VEGF are associated with a significantly greater likelihood of HAND, suggesting that interventions aimed at disordered iron transport and angiogenesis may be beneficial in this disorder.

Transition-transversion encoding and genetic relationship metric in ReliefF feature selection improves pathway enrichment in GWAS.

BACKGROUND: ReliefF is a nearest-neighbor based feature selection algorithm that efficiently detects variants that are important due to statistical interactions or epistasis. For categorical predictors, like genotypes, the standard metric used in ReliefF has been a simple (binary) mismatch difference. In this study, we develop new metrics of varying complexity that incorporate allele sharing, adjustment for allele frequency heterogeneity via the genetic relationship matrix (GRM), and physicochemical differences of variants via a new transition/transversion encoding. METHODS: We introduce a new two-dimensional transition/transversion genotype encoding for ReliefF, and we implement three ReliefF attribute metrics: 1.) genotype mismatch (GM), which is the ReliefF standard, 2.) allele mismatch (AM), which accounts for heterozygous differences and has not been used previously in ReliefF, and 3.) the new transition/transversion metric. We incorporate these attribute metrics into the ReliefF nearest neighbor calculation with a Manhattan metric, and we introduce GRM as a new ReliefF nearest-neighbor metric to adjust for allele frequency heterogeneity. RESULTS: We apply ReliefF with each metric to a GWAS of major depressive disorder and compare the detection of genes in pathways implicated in depression, including Axon Guidance, Neuronal System, and G Protein-Coupled Receptor Signaling. We also compare with detection by Random Forest and Lasso as well as random/null selection to assess pathway size bias. CONCLUSIONS: Our results suggest that using more genetically motivated encodings, such as transition/transversion, and metrics that adjust for allele frequency heterogeneity, such as GRM, lead to ReliefF attribute scores with improved pathway enrichment.

Trans-ethnic analysis of metabochip data identifies two new loci associated with BMI.

OBJECTIVE: Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population. SUBJECTS: Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models. RESULTS: We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10-7). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue. CONCLUSION: Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.

Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network.

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE-PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of "precision medicine." The February 2015 eMERGE-PGx data release includes sequence-derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation-Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

A knowledge-driven interaction analysis reveals potential neurodegenerative mechanism of multiple sclerosis susceptibility.

Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of genome-wide association studies (GWAS). In addition to detecting epistasis, a benefit to interaction analysis is that it also increases power to detect weak main effects. We conducted a knowledge-driven interaction analysis of a GWAS of 931 multiple sclerosis (MS) trios to discover gene-gene interactions within established biological contexts. We identify heterogeneous signals, including a gene-gene interaction between CHRM3 (muscarinic cholinergic receptor 3) and MYLK (myosin light-chain kinase) (joint P=0.0002), an interaction between two phospholipase C-ß isoforms, PLCß1 and PLCß4 (joint P=0.0098), and a modest interaction between ACTN1 (actinin alpha 1) and MYH9 (myosin heavy chain 9) (joint P=0.0326), all localized to calcium-signaled cytoskeletal regulation. Furthermore, we discover a main effect (joint P=5.2E-5) previously unidentified by single-locus analysis within another related gene, SCIN (scinderin), a calcium-binding cytoskeleton regulatory protein. This work illustrates that knowledge-driven interaction analysis of GWAS data is a feasible approach to identify new genetic effects. The results of this study are among the first gene-gene interactions and non-immune susceptibility loci for MS. Further, the implicated genes cluster within inter-related biological mechanisms that suggest a neurodegenerative component to MS.

Elevation of IgA levels in the non-insulin-dependent (type II) diabetic patient.

Serum immunoglobulin (G, A, M) levels were performed on 66 patients with non-insulin-dependent (type II) diabetes mellitus (NIDDM). When compared with 30 age-matched normal controls and 32 hospitalized controls there was no significant difference between the mean IgG and IgM levels. The IgA levels were significantly higher (P less than 0.005) in the diabetic group when compared with both control groups. This is true regardless of age, sex, duration of disease, and type of treatment (insulin/diet or oral hypoglycemic agents and/or diet). Thirty-six percent of the diabetic patients' IgA levels exceeded the mean +/- 2 SD of the normal control group. There were no significant differences in immunoglobulin levels between insulin-treated and non-insulin-treated diabetic groups. Since diabetic patients may have a number of secondary diseases, attempts were made to correlate the most common of these (acute and/or chronic bacterial infections, hypertension, arteriosclerotic heart disease, and diabetic neuropathy) with elevated IgA levels. Only IgA levels of diabetic patients with infections versus diabetic patients without infections were significantly different (P less than 0.05). However, IgA levels of uninfected diabetic patients remained significantly higher than those of normal controls (P less than 0.005), hospitalized controls (P less than 0.01), and hospitalized controls with bacterial infections (P less than 0.005). Possible reasons for the isolated elevations of IgA are discussed.

An evaluation of a C-reactive protein assay using a rate immunonephelometric procedure.

By using 20 repetitive assays at three levels of C-reactive protein control serum, within-run and day-to-day precision of a rate immunonephelometric system was established. The precision was excellent in each case. Linearity of the system between 1.8 and 20 mg/dl was established at a coefficient of correlation of 0.999 by using serial dilutions of C-reactive protein control serum. When the immunonephelometric assay was compared with electroimmunodiffusion and radial immunodiffusion assays, coefficients of correlation of 0.986 and 0.993, respectively, were obtained. The lower limit of sensitivity of the immunonephelometric assay was 1.8 mg/dl. The relationship of clinical significance to the performance of the C-reactive protein test system using rate immunonephelometry is discussed.