Genetic vulnerability factor for schizophrenia: association with glutamate cysteine ligase modifier gene and abnormal enzyme activity

Background: We previously reported in schizophrenia patients a decreased level of glutathione ([GSH]), the principal non-protein antioxidant and redox regulator, both in cerebrospinal-fluid and prefrontal cortex. To identify possible genetic causation, we studied genes involved in GSH metabolism. Methods: Genotyping: mass spectrometry analysis of polymerase chain reaction (PCR) amplified DNA fragments purified from peripheral blood. Gene expression: real-time PCR of total RNA isolated from fibroblast cultures derived from skin of patients (DSM-IV) and healthy controls (DIGS). Results: Case-control association study of single nucleotide polymorphisms (SNP) from the GSH key synthesizing enzyme glutamate-cysteine-ligase (GCL) modifier subunit (GCLM) was performed in two populations: Swiss (patients/controls: 40/31) and Danish (349/348). We found a strong association of SNP rs2301022 in GCLM gene (Danish: c2=3.2; P=0.001 after correction for multiple testing). Evidence for GCLM as a risk factor was confirmed in linkage study of NIMH families. Moreover, we observed a decrease in GCLM mRNA levels in patient fibroblasts, consistently with the association study. Interestingly, Dalton and collaborators reported in GCLM knock-out mice an increased feedback inhibition of GCL activity, resulting in 60% decrease of brain [GSH], a situation analogous to patients. These mice also exhibited an increased sensitivity to oxidative stress. Similarly, under oxidative stress conditions, GCL enzymatic activity was also decreased in patient fibroblasts. Conclusions: These results at the genetic and functional levels, combined with observations that GSH deficient models reveal morphological, electrophysiological, and behavioral anomalies analogous to those observed in patients, suggest that GCLM allelic variant is a vulnerability factor for schizophrenia.

A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control.

HIV-1 sequence diversity is affected by selection pressures arising from host genomic factors. Using paired human and viral data from 1071 individuals, we ran >3000 genome-wide scans, testing for associations between host DNA polymorphisms, HIV-1 sequence variation and plasma viral load (VL), while considering human and viral population structure. We observed significant human SNP associations to a total of 48 HIV-1 amino acid variants (p<2.4 × 10(-12)). All associated SNPs mapped to the HLA class I region. Clinical relevance of host and pathogen variation was assessed using VL results. We identified two critical advantages to the use of viral variation for identifying host factors: (1) association signals are much stronger for HIV-1 sequence variants than VL, reflecting the 'intermediate phenotype' nature of viral variation; (2) association testing can be run without any clinical data. The proposed genome-to-genome approach highlights sites of genomic conflict and is a strategy generally applicable to studies of host-pathogen interaction. DOI:http://dx.doi.org/10.7554/eLife.01123.001.

The genetic structure of metapopulations and conservation biology.

A range of models describing metapopulations is surveyed and their implications for conservation biology are described. An overview of the use of both population genetic elements and demographic theory in metapopulation models is given. It would appear that most of the current models suffer from either the use of over-simplified demography or the avoidance of selectively important genetic factors. The scale for which predictions are made by the various models is often obscure. A conceptual framework for describing metapopulations by utilising the concept of fitness of local populations is provided and some examples are given. The expectation that any general theory, such as that of metapopulations, can make useful predictions for particular problems of conservation is examined and compared with the prevailing 'state of the art' recommendations.

Genetic evidence for a role of adiponutrin in the metabolism of apolipoprotein B-containing lipoproteins.

Adiponutrin (PNPLA3) is a predominantly liver-expressed transmembrane protein with phospholipase activity that is regulated by fasting and feeding. Recent genome-wide association studies identified PNPLA3 to be associated with hepatic fat content and liver function, thus pointing to a possible involvement in the hepatic lipoprotein metabolism. The aim of this study was to examine the association between two common variants in the adiponutrin gene and parameters of lipoprotein metabolism in 23,274 participants from eight independent West-Eurasian study populations including six population-based studies [Bruneck (n = 800), KORA S3/F3 (n = 1644), KORA S4/F4 (n = 1814), CoLaus (n = 5435), SHIP (n = 4012), Rotterdam (n = 5967)], the SAPHIR Study as a healthy working population (n = 1738) and the Utah Obesity Case-Control Study including a group of 1037 severely obese individuals (average BMI 46 kg/m2) and 827 controls from the same geographical region of Utah. We observed a strong additive association of a common non-synonymous variant within adiponutrin (rs738409) with age-, gender-, and alanine-aminotransferase-adjusted lipoprotein concentrations: each copy of the minor allele decreased levels of total cholesterol on average by 2.43 mg/dl (P = 8.87 x 10(-7)), non-HDL cholesterol levels by 2.35 mg/dl (P = 2.27 x 10(-6)) and LDL cholesterol levels by 1.48 mg/dl (P = 7.99 x 10(-4)). These associations remained significant after correction for multiple testing. We did not observe clear evidence for associations with HDL cholesterol or triglyceride concentrations. In conclusion, our study suggests that adiponutrin is involved in the metabolism of apoB-containing lipoproteins.

Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study.

The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10(-8)) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10(-8)). The top IBC association for SBP was rs2012318 (P= 6.4 × 10(-6)) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10(-6)) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexity.

Inferring landscape effects on dispersal from genetic distances: how far can we go?

Functional connectivity affects demography and gene dynamics in fragmented populations. Besides species-specific dispersal ability, the connectivity between local populations is affected by the landscape elements encountered during dispersal. Documenting these effects is thus a central issue for the conservation and management of fragmented populations. In this study, we compare the power and accuracy of three methods (partial correlations, regressions and Approximate Bayesian Computations) that use genetic distances to infer the effect of landscape upon dispersal. We use stochastic individual-based simulations of fragmented populations surrounded by landscape elements that differ in their permeability to dispersal. The power and accuracy of all three methods are good when there is a strong contrast between the permeability of different landscape elements. The power and accuracy can be further improved by restricting analyses to adjacent pairs of populations. Landscape elements that strongly impede dispersal are the easiest to identify. However, power and accuracy decrease drastically when landscape complexity increases and the contrast between the permeability of landscape elements decreases. We provide guidelines for future studies and underline the needs to evaluate or develop approaches that are more powerful.