The Role of Variation at AβPP, PSEN1, PSEN2, and MAPT in Late Onset Alzheimer's Disease

Rare mutations in AßPP, PSEN1, and PSEN2 cause uncommon early onset forms of Alzheimer's disease (AD), and common variants in MAPT are associated with risk of other neurodegenerative disorders. We sought to establish whether common genetic variation in these genes confer risk to the common form of AD which occurs later in life (>65 years). We therefore tested single-nucleotide polymorphisms at these loci for association with late-onset AD (LOAD) in a large case-control sample consisting of 3,940 cases and 13,373 controls. Single-marker analysis did not identify any variants that reached genome-wide significance, a result which is supported by other recent genome-wide association studies. However, we did observe a significant association at the MAPT locus using a gene-wide approach (p = 0.009). We also observed suggestive association between AD and the marker rs9468, which defines the H1 haplotype, an extended haplotype that spans the MAPT gene and has previously been implicated in other neurodegenerative disorders including Parkinson's disease, progressive supranuclear palsy, and corticobasal degeneration. In summary common variants at AßPP, PSEN1, and PSEN2 and MAPT are unlikely to make strong contributions to susceptibility for LOAD. However, the gene-wide effect observed at MAPT indicates a possible contribution to disease risk which requires further study.

Mood congruent psychotic symptoms and specific cognitive deficits in carriers of the novel schizophrenia risk variant at MIR-137

Objective: The Schizophrenia Psychiatric Genome-wide Association (GWAS) Consortium recently reported on five novel schizophrenia susceptibility loci. The most significant finding mapped to a micro-RNA, MIR-137, which may be involved in regulating the function of other schizophrenia and bipolar disorder susceptibility genes. Method: We genotyped 821 patients with confirmed DSM-IV diagnoses of schizophrenia, bipolar affective disorder I and schizoaffective disorder for the risk SNP (rs1625579) and investigated the clinical profiles of risk allele carriers using a within-case design. We also assessed neurocognitive performance in a subset of cases (n=399) and controls (n=171). Results: Carriers of the risk allele had lower scores for an OPCRIT-derived positive symptom factor (p=0.04) and lower scores on a lifetime measure of psychosis incongruity (p=0.017). Risk allele carriers also had more cognitive deficits involving episodic memory and attentional control. Conclusion: This is the first evidence that the MIR-137 risk variant may be associated with a specific subgroup of psychosis patients. Although the effect of this single SNP was not clinically relevant, investigation of the impact of carrying multiple risk SNPs in the MIR-137 regulatory network on diagnosis and illness profile may be warranted. © 2012 Elsevier Ireland Ltd.

Design, recruitment, logistics, and data management of the GEHA (Genetics of Healthy Ageing) project

In 2004, the integrated European project GEHA (Genetics of Healthy Ageing) was initiated with the aim of identifying genes involved in healthy ageing and longevity. The first step in the project was the recruitment of more than 2500 pairs of siblings aged 90 years or more together with one younger control person from 15 areas in 11 European countries through a coordinated and standardised effort. A biological sample, preferably a blood sample, was collected from each participant, and basic physical and cognitive measures were obtained together with information about health, life style, and family composition. From 2004 to 2008 a total of 2535 families comprising 5319 nonagenarian siblings were identified and included in the project. In addition, 2548 younger control persons aged 50-75 years were recruited. A total of 2249 complete trios with blood samples from at least two old siblings and the younger control were formed and are available for genetic analyses (e.g. linkage studies and genome-wide association studies). Mortality follow-up improves the possibility of identifying families with the most extreme longevity phenotypes. With a mean follow-up time of 3.7 years the number of families with all participating siblings aged 95 years or more has increased by a factor of 5 to 750 families compared to when interviews were conducted. Thus, the GEHA project represents a unique source in the search for genes related to healthy ageing and longevity.

Seven new loci associated with age-related macular degeneration

Age-related macular degeneration (AMD) is a common cause of blindness in older individuals. To accelerate the understanding of AMD biology and help design new therapies, we executed a collaborative genome-wide association study, including >17,100 advanced AMD cases and >60,000 controls of European and Asian ancestry. We identified 19 loci associated at P <5 × 10(-8). These loci show enrichment for genes involved in the regulation of complement activity, lipid metabolism, extracellular matrix remodeling and angiogenesis. Our results include seven loci with associations reaching P <5 × 10(-8) for the first time, near the genes COL8A1-FILIP1L, IER3-DDR1, SLC16A8, TGFBR1, RAD51B, ADAMTS9 and B3GALTL. A genetic risk score combining SNP genotypes from all loci showed similar ability to distinguish cases and controls in all samples examined. Our findings provide new directions for biological, genetic and therapeutic studies of AMD.

Common variation near CDKN1A, POLD3 and SHROOM2 influences colorectal cancer risk.

We performed a meta-analysis of five genome-wide association studies to identify common variants influencing colorectal cancer (CRC) risk comprising 8,682 cases and 9,649 controls. Replication analysis was performed in case-control sets totaling 21,096 cases and 19,555 controls. We identified three new CRC risk loci at 6p21 (rs1321311, near CDKN1A; P = 1.14 × 10(-10)), 11q13.4 (rs3824999, intronic to POLD3; P = 3.65 × 10(-10)) and Xp22.2 (rs5934683, near SHROOM2; P = 7.30 × 10(-10)) This brings the number of independent loci associated with CRC risk to 20 and provides further insight into the genetic architecture of inherited susceptibility to CRC.

Five authors reply

We read with interest the comments offered by Drs. Hughes and Bradley (1) on our systematic review (2). Four single nucleotide polymorphisms (SNPs), rs9332739 and rs547154 in the complement component 2 gene (C2) and rs4151667 and rs641153 in the complement factor B gene (CFB), were pooled. Hughes and Bradley point out that we omitted the most common variant, rs12614. In fact, rs12614 is in high linkage disequilibrium (LD) with rs641153, which was included, and the major allele of both of these SNPs is in the range of 90% (population code, CEU, in the International HapMap Project (http://hapmap.ncbi.nlm.nih.gov/)). Moreover, our review was initiated in September 2010, at which point only 4 studies had published associations with rs12614, whereas 14 studies (n = 11,378) were available for rs641153. While it is true that both SNPs are better analyzed as a haplotype, these data were simply not available for pooling.
Hughes and Bradley also point out that we obtained and pooled new data that were not previously published. While it is recommended that contact with authors be completed as part of a comprehensive meta-analysis, we acknowledge that these additional data were not previously published and peer reviewed and, hence, do not have the same level of transparency. However, given that sample collections often increase over time and that the instrumentation for genotyping is continually improving, we thought that it would be advantageous to use the most recent information; this is a subjective decision.
We also agree that the allele frequencies given by Kaur et al. (3) were exactly opposite to those expected and were suggestive of strand flipping. However, we specifically queried this with the lead author on 2 separate occasions and were assured it was not.
Hughes and Bradley do make an interesting suggestion that SNPs in high LD should be used as a gauge of genotyping quality in HuGE reviews. This is an interesting idea but difficult to put into practice as the r2 parameter they propose as a measure of LD has some unusual properties. Although r2 is a measure of LD, it is also linked to the allele frequency; even small differences in allele frequencies between 2 linked SNPs can reduce the r2 dramatically. Wray (4) explored these effects and found that, at a baseline allele frequency of 10%, even a difference in allele frequency between 2 SNPs as small as 2% can drop the r2 value below 0.8. This degree of allele frequency difference is consistent with what could be expected for sampling error. Furthermore, when we look at 2 linked dialleleic SNPs, giving 4 possible haplotypes, the absence of 1 haplotype dramatically reduces r2, despite the 2 loci being in high LD as measured by D'. In fact, this is the situation for rs12614 and rs641153, where the low frequency of 1 haplotype means that the r2 is 0.01 but the D' is 1.
Hughes and Bradley also suggest consideration of genotype call rate restrictions as an inclusion criterion for metaanalysis. This would be more appropriate when focusing on genetic variants per se, as considered within the context of a genome-wide association study or other specific genetic analysis where large numbers of SNPs are evaluated (5).
The concerns raised by Hughes and Bradley reflect the limited ability of a meta-analysis based on summary data to tease out inconsistencies best identified at the individual level. We agree that SNPs in LD should be evaluated, but this will not necessarily be straightforward. A move to make genetic data sets publicly available, as in the Database of Genotypes and Phenotypes (http://www.ncbi.nlm.nih.gov/ gap), is a step in the right direction for greater transparency.

Genetic and Epigenetic Risk Factors for Diabetic Kidney Disease

Diabetes is increasing at daunting rates worldwide, and approximately 40% of affected individuals will develop kidney complications. Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease, and there are significant healthcare costs providing appropriate renal replacement therapies to affected individuals. For several decades, investigators have sought to discover inherited risk factors and biomarkers for DKD. In recent years, advances in high-throughput laboratory techniques and computational analyses, coupled with the establishment of multicenter consortia, have helped to identify genetic loci that are replicated across multiple populations. Several genome-wide association studies (GWAS) have been conducted for DKD with further meta-analysis of GWAS and comprehensive ”single gene” meta-analyses now published. Despite these efforts, much of the inherited predisposition to DKD remains unexplained. Meta-analyses and integrated–omics pathway studies are being used to help elucidate underlying genetic risks. Epigenetic phenomena are increasingly recognized as important drivers of disease risk, and several epigenome-wide association studies have now been completed. This review describes key findings and ongoing genetic and epigenetic initiatives for DKD.

A Variant in LDLR is Associated with Abdominal Aortic Aneurysm

Background—Abdominal aortic aneurysm (AAA) is a common cardiovascular disease among older people and demonstrates significant heritability. In contrast to similar complex diseases, relatively few genetic associations with AAA have been confirmed. We reanalysed our genome-wide study and carried through to replication suggestive discovery associations at a lower level of significance.

Methods and Results—A genome-wide association study was conducted using 1,830 cases from the UK, New Zealand and Australia with infra-renal aorta diameter =30mm or ruptured AAA and 5,435 unscreened controls from the 1958 Birth Cohort and National Blood Service cohort from the Wellcome Trust Case Control Consortium. Eight suggestive associations with P<1x10-4 were carried through to in silico replication in 1,292 AAA cases and 30,503 controls. One SNP associated with P<0.05 after Bonferroni correction in the in silico study underwent further replication (706 AAA cases and 1,063 controls from the UK, 507 AAA cases and 199 controls from Denmark and 885 AAA cases and 1,000 controls from New Zealand). Low density lipoprotein receptor (LDLR) rs6511720 A, was significantly associated overall and in three of five individual replication studies. The full study showed an association that reached genome-wide significance (odds ratio 0.76; 95% confidence interval 0.70 to 0.83; P=2.08x10-10).

Conclusions—LDLR rs6511720 is associated with abdominal aortic aneurysm. This finding is consistent with established effects of this variant on coronary artery disease. Shared aetiological pathways with other cardiovascular diseases may present novel opportunities for preventative and therapeutic strategies for AAA.

Molecular Validation of the Schizophrenia Spectrum

Background: Early descriptive work and controlled family and adoption studies support the hypothesis that a range of personality and nonschizophrenic psychotic disorders aggregate in families of schizophrenic probands. Can we validate, using molecular polygene scores from genome-wide association studies (GWAS), this schizophrenia spectrum? Methods: The predictive value of polygenic findings reported by the Psychiatric GWAS Consortium (PGC) was applied to 4 groups of relatives from the Irish Study of High-Density Schizophrenia Families (ISHDSF; N = s) differing on their assignment within the schizophrenia spectrum. Genome-wide single nucleotide polymorphism data for affected and unaffected relatives were used to construct per-individual polygene risk scores based on the PGC stage-I results. We compared mean polygene scores in the ISHDSF with mean scores in ethnically matched population controls (N = 929). Results: The schizophrenia polygene score differed significantly across diagnostic categories and was highest in those with narrow schizophrenia spectrum, lowest in those with no psychiatric illness, and in-between in those classified in the intermediate, broad, and very broad schizophrenia spectrum. Relatives of all of these groups of affected subjects, including those with no diagnosis, had schizophrenia polygene scores significantly higher than the control sample. Conclusions: In the relatives of high-density families, the observed pattern of enrichment of molecular indices of schizophrenia risk suggests an underlying, continuous liability distribution and validates, using aggregate common risk alleles, a genetic basis for the schizophrenia spectrum disorders. In addition, as predicted by genetic theory, nonpsychotic members of multiply-affected schizophrenia families are significantly enriched for replicated, polygenic risk variants compared with the general population.

Common variant at 16p11.2 conferring risk of psychosis

Epidemiological and genetic data support the notion that schizophrenia and bipolar disorder share genetic risk factors. In our previous genome-wide association (GWA) study, meta-analysis and follow-up (totaling as many as 18,206 cases and 42,536 controls), we identified four loci showing genome-wide significant association with schizophrenia. Here we consider a mixed schizophrenia and bipolar disorder (psychosis) phenotype (addition of 7,469 bipolar disorder cases, 1,535 schizophrenia cases, 333 other psychosis cases, 808 unaffected family members and 46,160 controls). Combined analysis reveals a novel variant at 16p11.2 showing genome-wide significant association (rs4583255[T], OR = 1.08, P = 6.6 × 10−11). The new variant is located within a 593 kb region that substantially increases risk of psychosis when duplicated. In line with the association of the duplication with reduced body mass index (BMI), rs4583255[T] is also associated with lower BMI (P = 0.0039 in the public GIANT consortium dataset; P = 0.00047 in 22,651 additional Icelanders).

Genetic Markers Enhance Coronary Risk Prediction in Men: The MORGAM Prospective Cohorts

Background: More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.

Methods: Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5-18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.

Results: Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50-59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.

Conclusions: Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.

Chromosome 2q31. 1 associates with ESRD in women with type 1 diabetes

Sex and genetic variation influence the risk of developing diabetic nephropathy and ESRD in patients with type 1 diabetes. We performed a genome-wide association study in a cohort of 3652 patients from the Finnish Diabetic Nephropathy (FinnDiane) Study with type 1 diabetes to determine whether sex-specific genetic risk factors for ESRD exist. A common variant, rs4972593 on chromosome 2q31. 1, was associated with ESRD in women (P

Genetics of New-Onset Diabetes after Transplantation

New-onset diabetes after transplantation is a common complication that reduces recipient survival. Research in renal transplant recipients has suggested that pancreatic ß-cell dysfunction, as opposed to insulin resistance, may be the key pathologic process. In this study, clinical and genetic factors associated with new-onset diabetes after transplantation were identified in a white population. A joint analysis approach, with an initial genome-wide association study in a subset of cases followed by de novo genotyping in the complete case cohort, was implemented to identify single-nucleotide polymorphisms (SNPs) associated with the development of new-onset diabetes after transplantation. Clinical variables associated with the development of diabetes after renal transplantation included older recipient age, female sex, and percentage weight gain within 12 months of transplantation. The genome-wide association study identified 26 SNPs associated with new-onset diabetes after transplantation; this association was validated for eight SNPs (rs10484821, rs7533125, rs2861484, rs11580170, rs2020902, rs1836882, rs198372, and rs4394754) by de novo genotyping. These associations remained significant after multivariate adjustment for clinical variables. Seven of these SNPs are associated with genes implicated in ß-cell apoptosis. These results corroborate recent clinical evidence implicating ß-cell dysfunction in the pathophysiology of new-onset diabetes after transplantation and support the pursuit of therapeutic strategies to protect ß cells in the post-transplant period.

Using ancestry-informative markers to identify fine structure across 15 populations of European origin

The Wellcome Trust Case Control Consortium 3 anorexia nervosa genome-wide association scan includes 2907 cases from 15 different populations of European origin genotyped on the Illumina 670K chip. We compared methods for identifying population stratification, and suggest list of markers that may help to counter this problem. It is usual to identify population structure in such studies using only common variants with minor allele frequency (MAF) >5%; we find that this may result in highly informative SNPs being discarded, and suggest that instead all SNPs with MAF >1% may be used. We established informative axes of variation identified via principal component analysis and highlight important features of the genetic structure of diverse European-descent populations, some studied for the first time at this scale. Finally, we investigated the substructure within each of these 15 populations and identified SNPs that help capture hidden stratification. This work can provide information regarding the designing and interpretation of association results in the International Consortia.