Henrik Ullum

Large recurrent microdeletions associated with schizophrenia.

Reduced fecundity, associated with severe mental disorders, places negative selection pressure on risk alleles and may explain, in part, why common variants have not been found that confer risk of disorders such as autism, schizophrenia and mental retardation. Thus, rare variants may account for a larger fraction of the overall genetic risk than previously assumed. In contrast to rare single nucleotide mutations, rare copy number variations (CNVs) can be detected using genome-wide single nucleotide polymorphism arrays. This has led to the identification of CNVs associated with mental retardation and autism. In a genome-wide search for CNVs associating with schizophrenia, we used a population-based sample to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring. The 66 de novo CNVs identified were tested for association in a sample of 1,433 schizophrenia cases and 33,250 controls. Three deletions at 1q21.1, 15q11.2 and 15q13.3 showing nominal association with schizophrenia in the first sample (phase I) were followed up in a second sample of 3,285 cases and 7,951 controls (phase II). All three deletions significantly associate with schizophrenia and related psychoses in the combined sample. The identification of these rare, recurrent risk variants, having occurred independently in multiple founders and being subject to negative selection, is important in itself. CNV analysis may also point the way to the identification of additional and more prevalent risk variants in genes and pathways involved in schizophrenia.

Effects of CCR5-Delta32, CCR2-64I, and SDF-1 3'A alleles on HIV-1 disease progression: An international meta-analysis of individual-patient data

The burgeoning information on the human genome creates opportunities and challenges for studies of disease associations. Because genetic differences often produce modest effects, many patients must be studied to reach definitive conclusions. In the absence of a single large study, meta-analysis of individual-patient data (13) from smaller studies offers a way to assemble an adequate sample size. This approach is based on a unifying protocol that has standardized analytic definitions. When the protocol is applied to data contributed by most investigators working in a field, this method can provide more convincing results than a simple pooling of data or a meta-analysis of published reports (3). A meta-analysis of individual-patient data is also superior to a meta-analysis of published reports for examining differences in reported results. Host genetic variability affects the risk for AIDS after infection with HIV-1, but the effect of specific alleles (that is, alternative forms of a gene that exist at a specific chromosomal location [locus]) has been inconsistent. C-C chemokine receptor 5 (CCR5) is a major co-receptor for HIV-1, but CCR5- 32, an allele that contains a 32base pair deletion, codes for a nonfunctional co-receptor (46). CCR5-32 homozygotes (people who inherited the CCR5-32 allele from both parents) are highly resistant to HIV-1 infection (47). CCR5-32 heterozygotes (people who inherited the CCR5-32 allele from one parent and a functional CCR5 allele from the other parent) are susceptible to HIV-1 infection; however, according to some reports (6, 820), they progress from HIV-1 infection to AIDS more slowly than persons with two normal CCR5 alleles (called wild-type individuals). CCR2b is a minor HIV-1 co-receptor. The gene that codes for this chemokine receptor has a variant allele (CCR2-64I) that may affect the risk for AIDS (21). Epidemiologic studies of CCR2-64I carriers have been inconsistent (1826), and in vitro studies have identified no functional differences between cells from CCR2-64I carriers and those from wild-type patients (27, 28). Stromal cellderived factor-1 (SDF-1) is the chemokine ligand of CXCR4, an important co-receptor for HIV-1 late in the disease course (29, 30). Homozygosity for the SDF-1 3A allele has been reported to slow disease progression (31), but not in all studies (18, 19, 3235). To address these inconsistencies, we conducted an international meta-analysis of individual-patient data on the CCR5, CCR2, and SDF-1 alleles; data were contributed by 19 teams of investigators. Methods Organization of the Meta-Analysis All research teams investigating associations of genetic alleles with the course of HIV-1 disease progression were invited to contribute individual-patient data to the International Meta-Analysis of HIV Host Genetics. Collaborating teams were identified through MEDLINE searches, cited references of retrieved papers, abstracts of major HIV-related meetings, and communication with investigators working in the field. The meta-analysis was also announced in Nature Medicine (36), on the Web site of the International Cochrane Collaboration, and at HIV scientific meetings. A common protocol was developed in collaboration with research teams identified through these efforts. The meta-analysis database remained open until 12 February 1999 for the collection of CCR5- 32 and CCR2-64I data; because most of the participating investigator teams evaluated SDF-1 3A after they studied CCR5-32 and CCR2-64I, we collected data on SDF-1 3A until 30 November 1999. Selection of Databases Prospective cohort studies of patients with HIV-1 infection were included in the analysis if they had collected information on the pertinent genotypes, as well as on the time from seroconversion or study entry to the development of AIDS and to death. We excluded studies if genetic data or time-to-event data were unavailable or if the participants were enrolled after 1 January 1996. We included casecontrol studies if they compared patients with rapid versus slower rates of progression. Casecontrol studies were analyzed separately from prospective cohort studies. Definitions and End Points The prospective cohort studies in our meta-analysis typically had follow-up visits every 6 months. Within each study, we divided the participants according to enrollment before (seroconverters) or after (seroprevalent patients) HIV-1 infection. For seroconverters, a negative result and a subsequent positive result on enzyme-linked immunosorbent assay (ELISA) and Western blot test were obtained after enrollment. We analyzed the data on a time scale that originated at the date of study entry for seroprevalent participants and at the estimated date of seroconversion (calculated as the midpoint between the last study visit at which the patient tested negative for HIV-1 and the first visit at which the patient tested positive for HIV-1) for the seroconverters. The cohorts differed little in the precision of the estimated date of seroconversion because semiannual data were typically available. Data for patients of European descent and data for patients of African descent (37) were considered separately. Our analysis examined four major outcomes: 1) time from seroconversion (or study entry) to the development of AIDS, according to 1987 criteria by the U.S. Centers for Disease Control and Prevention [38]; 2) time from seroconversion [or study entry] to death; 3) time from development of AIDS to death; and 4) serum or plasma HIV-1 RNA level, which was measured by using a consistent method within each study. For seroconverters, we used the first measurement of HIV-1 RNA level recorded since onset of chronic HIV-1 infection (range, 6 to 42 months after the estimated date of seroconversion); for seroprevalent patients, we used the first study measurement of HIV-1 RNA level. We censored data on follow-up after 1 January 1996 to minimize the effects of potent antiretroviral therapy. The average follow-up to AIDS development or to the point of censoring in the CCR5- 32 and CCR2-64I analyses was 6.73 years for seroconverters and 6.37 years for seroprevalent patients; for the SDF-1 analysis, the average follow-up was 7.14 years for the seroconverters and 6.51 years for seroprevalent patients. We specified our outcome variables a priori and asked all investigators to contribute data in a format consistent with the protocol. Investigators at the coordinating center, which was located at the National Cancer Institute in Rockville, Maryland, communicated with the contributing investigators to verify that the data from each study adhered to the common definitions of the meta-analysis. The contributed data sets also underwent logical tests to identify internal inconsistencies or incompatibilities. Any missing information or errors in logic that were identified at the coordinating center were referred to the contributing investigators; all identified errors were resolved. Statistical Analysis We used Cox regression to determine hazard ratios (relative hazards) for the times to events for all study cohorts and subgroups (39). The hazard ratio approximates the relative risk or incidence risk ratio. A log10 transformation was used for all analyses of HIV-1 RNA level. Differences in HIV-1 RNA level within studies were analyzed as differences for independent samples of continuous variables. Pooled summary estimates of hazard ratios and differences of means were obtained by weighting estimates from each study by the inverse of its variance (1, 40). We estimated fixed effects and random effects (1, 40). Fixed-effects models assume that any differences in results among studies are simply due to chance, whereas random-effects models assume that there may be true differences in the results of different studies. We report random-effects estimates because these provide more conservative confidence intervals when the results are highly heterogeneous across cohorts. (In the absence of heterogeneity, fixed-effects and random-effects estimates coincide.) We assessed heterogeneity by using the Q statistic, which we considered to be significant if the P value was less than 0.10 (1). However, some cohorts had few SDF-1 3A homozygotes with clinical events. Therefore, we also calculated an efficient score test for heterogeneity on the basis of the appropriate interaction terms between genotype and cohort in a cohort-stratified proportional hazards model. Inferences were similar with both tests. To model the effect of rare genotypes (CCR2-64I homozygotes or patients who were heterozygous for CCR5- 32 and CCR2-64I), we fit Cox models to the pooled data from all cohort studies with stratification by study. For cohorts with no events among SDF-1 3A homozygotes, we estimated log relative hazards values on the basis of a penalized likelihood with a penalty term of 0.5 (log[1 + exp ()] ). Penalty terms shrink extreme values (which also have large variances) toward zero. Because these extreme estimates have small weights, they contribute little to the overall results. Their exclusion yielded results similar to those of the main analysis. All calculations were performed by using the MATLAB software package, version 5.3 (The MathWorks, Inc., Natick, Massachusetts). Results We restricted the main analysis of CCR5- 32 and CCR2-64I to patients of European or African descent with genotype data for both alleles (Table 1). Because CCR5- 32 and CCR2-64I are in complete linkage of disequilibrium (nonrandom association of alleles that lie close together on a chromosome) (21), the CCR5- 32 and CCR2-64I alleles are never found on the same paternal or maternal chromosome. Therefore, we compared patients with a variant allele to patients who were wild-type homozygotes for both CCR5 and CCR2. Because the CCR5- 32 allele is almost exclusively found in persons of European descent (46), the analysis of CCR5-32 was limited to such persons. The analysis of SDF-1 3A was limited to persons

Brain expressed microRNAs implicated in schizophrenia etiology.

Background Protein encoding genes have long been the major targets for research in schizophrenia genetics. However, with the identification of regulatory microRNAs (miRNAs) as important in brain development and function, miRNAs genes have emerged as candidates for schizophrenia-associated genetic factors. Indeed, the growing understanding of the regulatory properties and pleiotropic effects that miRNA have on molecular and cellular mechanisms, suggests that alterations in the interactions between miRNAs and their mRNA targets may contribute to phenotypic variation. Methodology/Principal Findings We have studied the association between schizophrenia and genetic variants of miRNA genes associated with brain-expression using a case-control study design on three Scandinavian samples. Eighteen known SNPs within or near brain-expressed miRNAs in three samples (Danish, Swedish and Norwegian: 420/163/257 schizophrenia patients and 1006/177/293 control subjects), were analyzed. Subsequently, joint analysis of the three samples was performed on SNPs showing marginal association. Two SNPs rs17578796 and rs1700 in hsa-mir-206 (mir-206) and hsa-mit-198 (mir-198) showed nominal significant allelic association to schizophrenia in the Danish and Norwegian sample respectively (P = 0.0021 & p = 0.038), of which only rs17578796 was significant in the joint sample. In-silico analysis revealed that 8 of the 15 genes predicted to be regulated by both mir-206 and mir-198, are transcriptional targets or interaction partners of the JUN, ATF2 and TAF1 connected in a tight network. JUN and two of the miRNA targets (CCND2 and PTPN1) in the network have previously been associated with schizophrenia. Conclusions/Significance We found nominal association between brain-expressed miRNAs and schizophrenia for rs17578796 and rs1700 located in mir-206 and mir-198 respectively. These two miRNAs have a surprising large number (15) of targets in common, eight of which are also connected by the same transcription factors.

NK cell response to physical activity : possible mechanisms of action

Natural killer (NK) cells are highly influenced by physical exercise. The possible important mechanisms behind exercise-induced changes in NK cell function are cytokines, hyperthermia, and stress hormones, including catecholamines, growth hormone, cortisol, and beta-endorphins. Infusion studies mimicking stress hormone levels in blood during exercise indicate that increased plasma-adrenaline accounts for at least part of the exercise-induced modulation of NK cell function. During moderate as well as severe acute exercise, the NK cell activity is enhanced, but severe exercise is followed by immunodepression, at least in part caused by prostaglandins. Elite athletes have at rest elevated NK cell activity. However, due to frequent severe exercise the NK cell function is often temporarily severely depressed. It is suggested that during the time of immunodepression microorganisms, especially virus, invade the host, whereby infections can be established. However, in those who perform regular moderate exercise the immune system will often be temporarily enhanced and this will protect these from infections.

Duration of red blood cell storage and survival of transfused patients (CME)

BACKGROUND: Disquieting reports of increased complication and death rates after transfusions of red blood cells (RBCs) stored for more than 14 days prompted us to perform an observational retrospective cohort study of mortality in relation to storage time.

Production of β-Chemokines in Human Immunodeficiency Virus (HIV) Infection: Evidence that High Levels of Macrophage Inflammatory Protein-1β Are Associated with a Decreased Risk of HIV Disease Progression

Macrophage inflammatory protein (MIP)-1alpha, MIP-1beta, and RANTES production were measured by ELISA in whole blood that had been stimulated for 4.5 h with phytohemagglutinin. The blood was from 90 healthy human immunodeficiency virus (HIV)-negative controls and from 245 HIV-infected subjects who were followed for < or = 4.5 years. HIV-infected persons without AIDS had increased levels of MIP-1alpha, MIP-1beta, and RANTES (P < .01) compared with levels in controls. Subjects with AIDS, compared with controls, had decreased production levels of MIP-1beta (P < .0001) and similar levels of MIP-1alpha and RANTES. A high level of MIP-1beta production was associated with a decreased risk of progressing to AIDS or death, as determined by univariate analysis (P < .01) and adjusted for CD4 cell count and age (P = .07, P = .06, respectively). The findings suggest that the production level of beta-chemokine changes during HIV infection and that a high level of beta-chemokine production in peripheral blood lymphocytes may be associated with less rapid disease progression in HIV infection.

International survey on NAT testing of blood donations: expanding implementation and yield from 1999 to 2009

International survey on NAT testing of blood donations : expanding implementation and yield from 1999 to 2009.

Schistosomiasis and HIV-1 Infection in Rural Zimbabwe: Effect of Treatment of Schistosomiasis on CD4 Cell Count and Plasma HIV-1 RNA Load

To determine whether treatment of schistosomiasis has an effect on the course of human immunodeficiency virus type 1 (HIV-1) infection, individuals with schistosomiasis and with or without HIV-1 infection were randomized to receive praziquantel treatment at inclusion or after a delay of 3 months; 287 participants were included in the study, and 227 (79%) were followed up. Among the 130 participants who were coinfected, those who received early treatment (n=64) had a significantly lower increase in plasma HIV-1 RNA load than did those who received delayed treatment (n=66) (P<.05); this difference was associated with no change in plasma HIV-1 RNA load in the early intervention group (P=.99) and an increase in plasma HIV-1 RNA load in the delayed intervention group (P<.01). Among the 227 participants who were followed up, those who received early treatment (n=105) had an increase in CD4 cell count, whereas those who received delayed treatment (n=122) did not (P<.05); this effect did not differ between participants when stratified by HIV-1 infection status (P=.17). The present study suggests that treatment of schistosomiasis can reduce the rate of viral replication and increase CD4 cell count in the coinfected host.

Conflicting Selective Forces Affect T Cell Receptor Contacts in an Immunodominant Human Immunodeficiency Virus Epitope.

Cytotoxic T lymphocytes (CTLs) are critical for the control of human immunodeficiency virus, but containment of virus replication can be undermined by mutations in CTL epitopes that lead to virus escape. We analyzed the evolution in vivo of an immunodominant, HLA-A2–restricted CTL epitope and found two principal, diametrically opposed evolutionary pathways that exclusively affect T cell–receptor contact residues. One pathway was characterized by acquisition of CTL escape mutations and the other by selection for wild-type amino acids. The pattern of CTL responses to epitope variants shaped which variant(s) prevailed in the virus population. The pathways notably influenced the amount of plasma virus, as patients with efficient CTL selection had lower plasma viral loads than did patients without efficient selection. Thus, viral escape from CTL responses does not necessarily correlate with disease progression.

The relative prognostic value of plasma HIV RNA levels and CD4 lymphocyte counts in advanced HIV infection

Objective:It has been suggested that the plasma HIV RNA level is a better predictor of AIDS and death than the CD4 lymphocyte count. We assessed whether the prognostic value of plasma virus levels was different according to the CD4 count. Design:Prospective cohort study of HIV-infected patients followed for a median of 2.91 years (range, 0.02–4.54). Setting:Department of Infectious Diseases at Rigshospitalet, Copenhagen, Denmark. Participants:A group of 255 HIV-infected individuals with an initial measurement of CD4 lymphocyte count and plasma HIV RNA. Main outcome measure:Survival time. Results:The plasma HIV RNA (median 101 410 copies/ml; range (range 200–7 200 000) and the CD4 lymphocyte count (median 250 cells × 106/l; range 1–1247) were negatively correlated (Pearson r = −0.53; P < 0.00001). Of the 255 patients, 110 died during follow-up. Overall, a higher HIV RNA level was associated with increased risk of death, but the association was smaller in patients with lower CD4 lymphocyte counts (test for interaction P < 0.0001). In patients with CD4 count below 50 cells × 106/l the association between HIV RNA and risk of death was not statistically significant (relative hazard per 10-fold higher HIV RNA level was 1.53; P = 0.11; adjusted for age and CD4 count) while that between the CD4 count and risk of death was highly significant (relative hazard per 50% lower CD4 count 1.38; P = 0.005; adjusted for age and HIV RNA level). Conclusions:Patients were relatively lightly treated with antiretroviral drugs both before and during this study. In this situation, it appears that the HIV RNA level has a relatively weak association with risk of death in patients with advanced HIV infection and that the CD4 lymphocyte count is probably more useful in assessing prognosis.