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Background: Recent meta‐analyses of genome‐wide association studies (GWAS) have identified ∼30 susceptibility LOAD loci in addition to APOE, however the majority are common variants (minor allele frequency (MAF)>0.02). We used the dense, high‐resolution Haplotype Reference Consortium (HRC) r1.1 reference panel (64,976 haplotypes/39,235,157 SNPs), which allows imputation of rare variants (MAF>0.0008), to impute 44 GWAS datasets of the IGAP consortia to identify novel rare variant, gene, and pathway associations. Method: We imputed 25,192 cases and 40,410 controls to the HRC r1.1 panel using Minimac3 on the Michigan Imputation Server. Converting imputed genotype probabilities to minor allele dosage, we ran logistic regression using SNPTEST on individual variants with MAF > 0.01 (and using generalized linear mixed models in R with family‐based datasets), and performed a fixed‐effects, inverse‐variance‐weighted meta‐analysis using METAL. Variants with MAF ≤ 0.01 were meta‐analyzed using score‐based tests via SeqMeta/R. Both analyses adjusted for age‐at‐onset(cases)/age‐at‐exam(controls), sex, and principal components for population substructure. Gene‐based associations were done with SKAT‐O and burden testing, while pathway associations were examined using VEGAS2. Result: Discovery analyses of ∼39.2M genotyped or imputed SNVs confirmed single variant associations in 26 of 30 known IGAP LOAD loci at suggestive levels of significance (P < 10−5), with 12 known loci attaining genome‐wide statistical significance (P < 5 × 10−8) (Figure 1). Newly observed associations included common variants (MAF>0.01) in or near homologs of known AD loci, EPHA5 (rs17086136, OR[95% CI] = 1.23 [1.13,1.33], P = 6.36 × 10−7) and ADAM28 (rs10096379, OR[95% CI] = 0.86 [0.81,0.92], P = 3.02 × 10−6); in/near neuronal development genes including DAB1 (neuronal migration; 1:57700874:T:G, OR[95% CI] = 0.71 [0.62, 0.81], P = 6.94 × 10−7) and DCC (axon guidance; rs2054289, OR[95% CI] = 0.71 [0.62, 0.83], P = 6.69 × 10−6); and in/near genes involved in cardiometabolic traits including THADA (type 2 diabetes; rs77101426, OR[95% CI] = 0.89 [0.85, 0.95], P = 2.37 × 10−6). Several known AD loci demonstrated novel rare variant associations with genome‐wide significance, including CR1, PICALM, and the MS4A region (Figure 2), and novel rare variant associations were observed in or near genes involved in memory and cognitive function, including HS3ST4 and DBX1. Independent replication in external datasets including the UK Biobank is on‐going. Conclusion: Several novel LOAD candidate loci, including those with prior associations with neurodevelopment and cardiometabolic traits, were identified using high‐quality imputation of rare and low‐frequency variants in IGAP. [ABSTRACT FROM AUTHOR]

Introduction: Exploring the role of Alzheimer's disease (AD) implicated pathways in the predementia phase may provide new insight for preventive and clinical trials targeting disease specific pathways. Methods: We constructed weighted Genetic risk scores, first based on 20 genome‐wide significant AD risk variants and second clustering these variants within pathways. Risk scores were investigated for their association with AD, mild cognitive impairment, and brain magnetic resonance imaging phenotypes including white matter lesions, hippocampal volume, and brain volume. Results: The risk score capturing endocytosis pathway was significantly associated with mild cognitive impairment (P = 1.44 × 10−4). Immune response (P =.016) and clathrin/AP2 adaptor complex pathway (P = 3.55 × 10−3) excluding apolipoprotein E also showed modest association with white matter lesions but did not sustain Bonferroni correction (P = 9.09 × 10−4). Discussion: Our study suggests that the clinical spectrum of early AD pathology is explained by different biological pathways, in particular, the endocytosis, clathrin/AP2 adaptor complex, and immune response pathways, that are independent of apolipoprotein E (APOE). [ABSTRACT FROM AUTHOR]

Background: Recent genome‐wide studies have identified over 70 risk loci for late onset Alzheimer's Disease (AD) (Kunkle et al. 2019, Bellenguez et el. 2021, Wightman et al. 2021). Analysis in this study focused on developing Machine Learning (ML) models to predict AD risk from genetic data. We compared the prediction accuracy of ML to polygenic risk scores (PRS) using SNPs in disease‐associated biological pathways. Method: We used the Genetic and Environmental Risk for Alzheimer's Disease consortium dataset (Harold et al. 2009). SNPs were selected from the AD associated pathways in Kunkle et al. 2019. Two decision tree‐based ML algorithms were used, Random Forests (RFs) and Gradient Boosting (GB). The prediction ability of these methods was compared to Polygenic Risk Score (PRS). RFs and GB models were developed using the Python library sklearn. These were trained and tested using 5‐fold cross‐validation. Clumping and thresholding (CT), as implemented in PLINK, was used to generate PRS, with logistic regression used for prediction. CT PRS was compared to the PRS generated by the PRS‐CS method (Ge, T., Chen, CY., Ni, Y. et al). Result: Initial results demonstrate that PRS, PRS‐CS and ML perform similarly for pathway specific analysis (AUC∼69%) when pathways include APOE. Conclusion: Subsequent analyses will compare the performance of the methods when APOE SNPs are removed from the pathways, and in multivariate analyses modelling multiple pathway effects simultaneously. [ABSTRACT FROM AUTHOR]

Huntington’s disease (HD) is an inherited neurodegeneration that causes a severe progressive illness and early death. Several animal models of the disease have been generated carrying the causative mutation and these have shown that one of the earliest molecular signs of the disease process is a substantial transcriptional deficit. We examined the alterations in brain gene expression in the R6/1 mouse line over the course of the development of phenotypic signs from 18 to 27 weeks. Changes in R6/1 mice were similar to those previously reported in R6/2 mice, and gene ontology analysis shows that pathways related to intracellular and electrical signaling are altered among downregulated genes and lipid biosynthesis and RNA processes among upregulated genes. The R6/1 mice showed deficits in rotarod performance, locomotor activity and exploratory behavior over the time–course. We have correlated the alterations in gene expression with changes in behavior seen in the mice and find that few alterations in gene expression correlate with all behavioral changes but rather that different subsets of the changes are uniquely correlated with one behavior only. This indicates that multiple behavioral tasks assessing different behavioral domains are likely to be necessary in therapeutic trials in mouse models of HD. [ABSTRACT FROM AUTHOR]

Traditionally in genetic case-control studies controls have been screened to exclude subjects with a personal history of illness. This control group has the advantage of optimal power to detect loci involved in illness, but requires more work and may incur substantial cost in recruitment. An alternative approach to screening is to use unscreened controls sampled from the general population. Such controls are generally plentiful and inexpensive, but in general there is a risk that some may have the same disease as the cases, which will reduce power to detect associations. We have quantified the extent of this power loss, and produced mathematical formulae for the number of unscreened controls necessary to achieve the same power as a fixed sample of screened controls. The effect of using unscreened controls will also depend on the ratio of the number of screened controls to cases specified in the original study design, and this is also investigated. We have also investigated the cost-benefits of the screened and unscreened approaches, according to variation in the relative costs of sampling screened and unscreened controls, together with genotyping costs. We have, thus, identified the range of situations in which using unscreened controls is a cost-effective alternative to the screened control method and could be considered when designing a study. In many of the typical, real-world situations in complex genetics, the use of unscreened controls is potentially cost-effective and can, in general, be considered for disorders with population prevalence Kp < 0.2. With the steady reduction in genotyping costs and the availability of common sets of “population controls” this design is likely to become increasingly cost effective. [ABSTRACT FROM AUTHOR]

A commonly-used method for testing for association between disease and a single-nucleotide polymorphism (SNP) is to compare the frequencies of the SNP genotypes in a sample of unrelated cases to those in a sample of unrelated controls drawn from the same population (an unmatched case-control study). A drawback of such a study is that it is impossible to detect genotyping errors, and few methods have been developed to allow for the presence of undetected genotyping errors. In this paper, we obtain analytic formulae for estimates of genotypic relative risks in terms of error probability (e). In general, e will be unknown. We investigate the effect of assuming both correct and incorrect values of e on power and type I error, and also on the genotypic relative risk estimates. The choice of e was found to have no effect on power or Type I error probability (provided a 2df test was used, allowing relative risks of homozygotes and heterozygotes to differ). However, overestimating e in the presence of a true association was found in general to bias relative risk estimates away from the null, with underestimates ore having the opposite effect. Although e is unknown, it may be estimated from an external "validation" study, such as genotyping a sample of unrelated individuals twice and counting the discrepancies. Simulation results suggest that, for such a study, 25 individuals would be sufficient to give approximately unbiased estimates of relative risks. [ABSTRACT FROM AUTHOR]

Background: The rate of cognitive decline in Alzheimer's disease (AD) has been found to vary widely between individuals, with numerous factors driving this heterogeneity. This study aims to explore the genetic architecture of cognitive decline in AD. Methods: We used a subset of 543 individuals with AD from the GERAD cohort (Harold et al., 2009) and a subset of 180 individuals with AD from the ADNI dataset (Mueller et al., 2005) with genetic data and cognitive assessments at multiple timepoints. Firstly, a metric of cognitive decline for each individual was estimated as the random slope from a random effects regression model of Mini Mental State Examination (MMSE) scores. This metric was consequently used to perform genome‐wide association studies of cognitive decline in each dataset, which were then meta‐analysed. Two polygenic risk score (PRS) analyses were performed, one exploring the polygenic heritability of decline in AD and the other examining the shared genetic architecture between decline and AD risk, based on the latest AD GWAS (Kunkle et al., 2019). Results: Meta‐analysis revealed 8 variants reaching genome‐wide significance. Rate of decline PRS based on summary statistics from the GERAD data was not associated with decline in the ADNI dataset. Finally, AD risk PRS was not associated with rate of decline in either dataset. Conclusions: The lack of association of the AD risk PRS with rate of decline might indicate that the genetic risk for accelerated cognitive decline within AD is separate from the genetic risk for developing AD. The power of this study is limited by the small sample sizes, and replication in a larger dataset is necessary both to validate these findings and uncover additional variants that affect the rate of decline in AD. [ABSTRACT FROM AUTHOR]

Background: The rate of disease progression is an important factor to consider regarding Alzheimer's disease (AD), as people with a rapid decline are considerably more likely to require additional care resources. The rate of progression in AD has been found to vary widely between individuals, with numerous factors driving this heterogeneity. In this project, a genome‐wide association study (GWAS) was performed to investigate the presence of a genetic liability to faster progression in patients with AD. Methods: A subset of 543 individuals with AD from the Cardiff MRC centre cohorts that have been assessed at multiple timepoints was used in this analysis. A progression score for each individual was approximated by a random slope from a random effects regression model of Mini Mental State Examination (MMSE) using all available MMSE measurements. The score was subsequently used in a GWAS of progression. Quality control analysis was performed following standard GWAS protocols resulting in 304,448 variants to be included in the analysis. Results: The sample was 67.37% female, with mean age at recruitment being 80.2 years. Mean MMSE was 17.03 at first assessment and 11.54 at last assessment, and mean number of assessments was 3.16. After correcting for multiple testing, no variant was found to be significantly associated with progression in this GWAS. Furthermore, apolipoprotein E (ApoE) genotype was not associated with progression. Conclusion: Preliminary results show that, after Bonferroni correction for multiple testing, no variant was significantly associated with progression in AD. Suggestive associated variants were found in chromosome 20:5843812 (p‐value = 3.12 × 10−7), 1:62271962 (p‐value = 6.30 × 10−7), 10:15452800 (p‐value = 1.65 × 10−6) and 5:117646945 (p‐value = 2.40 × 10−6). Moreover, ApoE genotype was not found to affect the rate progression, the lowest p‐value in the ApoE region (19:44905791 ‐ 19:44909393) being 0.23. This non‐significant result might indicate that the genetic risk for accelerated cognitive decline within AD is separate from the genetic risk for developing AD. The sample size is one of the main limitations of this study. Replication in a larger dataset is necessary in order to validate these findings and uncover the presence of genetic variants that affect the rate of decline in AD. [ABSTRACT FROM AUTHOR]

The comprehensive genome-wide nature of transcriptome studies in Alzheimer's disease (AD) should provide a reliable description of disease molecular states. However, the genes and molecular systems nominated by transcriptomic studies do not always overlap. Even when results do align, it is not clear if those observations represent true consensus across many studies. A couple of sources of variation have been proposed to explain this variability, including tissue-of-origin and cohort type, but its basis remains uncertain. To address this variability and extract reliable results, we utilized all publicly available blood or brain transcriptomic datasets of AD, comprised of 24 brain studies with 4007 samples from six different brain regions, and eight blood studies with 1566 samples. We identified a consensus of AD-associated genes across brain regions and AD-associated gene-sets across blood and brain, generalizable machine learning and linear scoring classifiers, and significant contributors to biological diversity in AD datasets. While AD-associated genes did not significantly overlap between blood and brain, our findings highlighted 15 dysregulated processes shared across blood and brain in AD. The top five most significantly dysregulated processes were DNA replication, metabolism of proteins, protein localization, cell cycle, and programmed cell death. Conversely, addressing the discord across studies, we found that large-scale gene co-regulation patterns can account for a significant fraction of variability in AD datasets. Overall, this study ranked and characterized a compilation of genes and molecular systems consistently identified across a large assembly of AD transcriptome studies in blood and brain, providing potential candidate biomarkers and therapeutic targets., (© 2024 Wiley Periodicals LLC.)

Identifying heritable factors that moderate the genetic risk for schizophrenia (SCZ) could help clarify why some individuals remain unaffected despite having relatively high genetic liability. Previously, we developed a framework to mine genome-wide association (GWAS) data for common genetic variants that protect high-risk unaffected individuals from SCZ, leading to derivation of the first-ever "polygenic resilience score" for SCZ (resilient controls n = 3786; polygenic risk score-matched SCZ cases n = 18,619). Here, we performed a replication study to verify the moderating effect of our polygenic resilience score on SCZ risk (OR = 1.09, p = 4.03 × 10 -5 ) using newly released GWAS data from 23 independent case-control studies collated by the Psychiatric Genomics Consortium (PGC) (resilient controls n = 2821; polygenic risk score-matched SCZ cases n = 5150). Additionally, we sought to optimize our polygenic resilience-scoring formula to improve subsequent modeling of resilience to SCZ and other complex disorders. We found significant replication of the polygenic resilience score, and found that strict pruning of SNPs based on linkage disequilibrium to known risk SNPs and their linked loci optimizes the performance of the polygenic resilience score., (© 2023 Wiley Periodicals LLC.)

A major controversy in psychiatric genetics is whether nonadditive genetic interaction effects contribute to the risk of highly polygenic disorders. We applied a support vector machines (SVMs) approach, which is capable of building linear and nonlinear models using kernel methods, to classify cases from controls in a large schizophrenia case-control sample of 11,853 subjects (5,554 cases and 6,299 controls) and compared its prediction accuracy with the polygenic risk score (PRS) approach. We also investigated whether SVMs are a suitable approach to detecting nonlinear genetic effects, that is, interactions. We found that PRS provided more accurate case/control classification than either linear or nonlinear SVMs, and give a tentative explanation why PRS outperforms both multivariate regression and linear kernel SVMs. In addition, we observe that nonlinear kernel SVMs showed higher classification accuracy than linear SVMs when a large number of SNPs are entered into the model. We conclude that SVMs are a potential tool for assessing the presence of interactions, prior to searching for them explicitly., (© 2018 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics published by Wiley Periodicals, Inc.)

Strong evidence that rare variants of relatively high penetrance are involved in the etiology of schizophrenia is currently restricted to the data from studies investigating copy number variants and major structural re-arrangements in that disorder. Global tests of the hypothesis of the involvement of fairly high penetrance rare single nucleotide changes or small insertion deletion events await the genesis of data from large-scale sequencing studies, meanwhile, a pragmatic approach to trying to detect such alleles is to target sequencing efforts on genes for which there is compelling evidence from other sources for their involvement in this disorder. We have undertaken a study, which aimed to identify whether rare (frequency ∼0.001%) coding variants in the schizophrenia susceptibility gene ZNF804A are involved in this disorder. We screened the coding regions of the gene in 517 schizophrenic cases and 501 controls, and genotyped rare non-synonymous variants in a case-control sample powered to detect association to rare alleles with an effect size (odds ratio) of 5. No single rare variant was associated with schizophrenia, nor was the burden of rare, or even fairly common, non-synonymous variants. Our results do not support the hypothesis that moderately rare non-synonymous variants at the ZNF804A locus are involved in schizophrenia susceptibility. © 2010 Wiley-Liss, Inc., (Copyright © 2010 Wiley-Liss, Inc.)

Variation in incidence of schizophrenia between populations with different ethnical background may reflect population specific differences in nature and composition of genetic and environmental factors. In order to investigate whether there are population specific susceptibility genes for schizophrenia, we collected in Indonesia families with two or more affected siblings and, as far as available, parents and unaffected siblings, suitable for genetic linkage- and association studies. After checking extensively for incompatibilities with Mendelian inheritance as well as for errors in sampling, we used 124 families from the sample of 152 originally ascertained families for linkage analysis. Genotyping was performed at the NHLBI Mammalian Genotyping Service at Marshfield Research Organisation using the Screening Set 16, which comprises 402 Short Tandem Repeat Polymorphisms (STRPs). The genotypes of 540 individuals including 267 affected with schizophrenia were used for analysis. Multipoint sib-pair linkage analysis was carried out by estimation of--allele sharing derived--maximum likelihood LOD scores (MLS) in 154 sib-pair combinations. We obtained a genome-wide significant MLS of 3.76 on chromosome 3p26.2-25.3. Genome-wide significance was estimated by performing 10,000 simulated genomescans. Additional loci were detected on 1p12, which produced suggestive evidence for linkage (MLS = 2.35), as well as on 5q14.1 (MLS = 1.56), 5q33.3 (MLS = 1.11), and 10q (MLS = 1.17), where linkage had been reported previously. In conclusion, our study detected a region with genome-wide significant linkage, which will serve as starting point for identification of schizophrenia susceptibility genes in the Indonesian population.

We have studied the impact of the apolipoprotein E gene (APOE) on the chromosome 19 linkage peak from an analysis of sib-pairs affected by Alzheimer's disease. We genotyped 417 affected sib-pairs (ASPs) collected in Sweden and Norway (SWE), the UK and the USA for 10 microsatellite markers on chromosome 19. The highest Zlr (3.28, chromosome-wide P-value 0.036) from the multipoint linkage analysis was located approximately 1 Mb from APOE, at marker D19S178. The linkage to chromosome 19 was well explained by APOE in the whole sample as well as in the UK and USA subsamples, as identity by descent (IBD) increased with the number of epsilon4 alleles in ASPs. There was a suggestion from the SWE subsample that linkage was higher than would be expected from APOE alone, although the test for this did not reach formal statistical significance. There was also a significant age at onset (aao) effect on linkage to chromosome 19q13 in the whole sample, which manifested itself as increased IBD sharing in relative pairs with lower mean aao. This effect was partially, although not completely, explained by APOE. The aao effect varied considerably between the different subsamples, with most of the effect coming from the UK sample. The other samples showed smaller effects in the same direction, but these were not significant., (2007 Wiley-Liss, Inc.)

Gene x environment (G x E) interactions are increasingly thought to have substantial influence on the aetiology and clinical manifestations of complex disorders. In ADHD, although main effects of specific genetic variants and pre- or peri-natal variables have been reported and replicated using pooled analyses, few studies have looked at possible interactions. In a clinical sample of 266 children with ADHD, we tested for interaction between gene variants (in DRD4, DAT1, DRD5, and 5HTT) found to be associated with ADHD in pooled analyses and maternal smoking, alcohol use during pregnancy and birth weight. First, G x E effects on a diagnosis of ADHD were tested using conditional logistic regression analyses. Second, possible modifying effects of G x E on symptoms of associated conduct disorder and oppositional defiant disorder (ODD) were investigated using linear regression analysis. The sample size associated with each of the analyses differed as not each variant had been genotyped for each individual. No effects of G x E on ADHD diagnosis were observed. The results suggest that lower birth weight and maternal smoking during pregnancy may interact with DRD5 and DAT1 (birth weight only) in influencing associated antisocial behavior symptoms (ODD and conduct disorder). These preliminary findings showed no evidence of interaction between previously implicated variants in ADHD and specific environmental risk factors, on diagnosis of the disorder. There may be evidence of G x E on associated antisocial behavior in ADHD, but further investigation is needed., ((c) 2007 Wiley-Liss, Inc.)

Recent evidence suggests a potential role for the p11 gene in conferring risk to depressive disorders. p11 has been shown to influence serotonergic transmission, and its expression was found to be reduced in a mouse model of depression, as well as in post-mortem brain tissue from major depressive disorder (MDD) cases. In the present study, we tested for rare variants in p11 by resequencing promoter, exonic and flanking intronic regions in 176 MDD cases and 176 matched controls. We also assessed common variation by genotyping eight single nucleotide polymorphisms (SNPs), seven tag SNPs and one found through resequencing, in 641 cases and 650 controls. Resequencing revealed nine novel rare variants, including a missense mutation (Asp60Glu) observed in one case and one control, and four variants that occurred only in cases and not controls. The number of rare variants in cases did not exceed that expected by chance for the length of sequence analyzed, and also was not significantly greater than that observed in controls. Resequencing also identified two known SNPs, one (rs4845720) of which was significantly more frequent in cases than controls in the resequenced sample (3.1% vs. 0.9%, P = 0.03), though not in the larger sample (3% vs. 2%, P = 0.15). None of the tag SNPs showed any evidence of association. Our results do not support a major role for either common or rare p11 SNPs with MDD. Several limitations of the study are discussed., (2007 Wiley-Liss, Inc.)

Psychotic symptoms are common in Alzheimer's disease (AD) and are associated with increased cognitive impairment and earlier institutionalization. One study has suggested that they are genetically modified and two genome screens have been performed to search for susceptibility loci for AD with psychosis (AD + P). The aim of this study was to further investigate the familial aggregation of AD + P and perform a genome screen for AD, conditioning on the presence or absence of psychotic symptoms. Samples from the UK and US were combined, providing data from 374 families in which at least two members met criteria for AD and had complete data regarding psychotic symptoms. Generalized estimating equations (GEE) were used to assess the relationship of psychotic symptoms between siblings. A total of 321 affected relative pairs (ARPs) were genotyped for linkage. There was a significant association between proband psychosis status and the occurrence of AD + P in siblings in the UK (OR = 4.17, P = 0.002) and US (OR = 3.2, P < 0.001) samples. Chromosomewide and genomewide significant linkage peaks were observed on chromosomes 7 (LOD = 2.84) and 15 (LOD = 3.16), respectively, with the strongest evidence coming from pairs concordant for AD without psychosis. A LOD score of 2.98 was observed close to a previously reported AD + P linkage region on chromosome 6, however the increase in LOD attributable to psychosis was not significant. These findings support the hypothesis that psychotic symptoms in AD are genetically modified and that a gene/s implicated in their aetiology may be located on chromosome 7 and 15., ((c) 2007 Wiley-Liss, Inc.)

Linkage studies have suggested there is a susceptibility gene for late onset Alzheimer's disease (LOAD) in a broad region of chromosome 10. A strong positional and biological candidate is the gene encoding the insulin-degrading enzyme (IDE), a protease involved in the catabolism of Abeta. However, previous association studies have produced inconsistent results. To systematically evaluate the role of variation in IDE in the risk for LOAD, we genotyped 18 SNPs spanning a 276 kb region in and around IDE, including three "tagging" SNPs identified in an earlier study. We used four case-control series with a total of 1,217 cases and 1,257 controls. One SNP (IDE&#95;7) showed association in two samples (P-value = 0.0066, and P = 0.026, respectively), but this result was not replicated in the other two series. None of the other SNPs showed association with LOAD in any of the tested samples. Haplotypes, constructed from the three tagging SNPs, showed no globally significant association. In the UK2 series, the CTA haplotype was over-represented in cases (P = 0.046), and in the combined data set, the CCG haplotype was more frequent in controls (P = 0.015). However, these weak associations observed in our series were in the opposite direction to the results in previous studies. Although our results are not universally negative, we were unable to replicate the results of previous studies and conclude that common variants or haplotypes of these variants in IDE are not major risk factors for LOAD., (Copyright 2005 Wiley-Liss, Inc.)

We performed an affected sib-pair (ASP) linkage analysis to test for the effects of age at onset (AAO), rate of decline (ROD), and Apolipoprotein E (APOE) genotype on linkage to late-onset Alzheimer's disease (AD) in a sample comprising 428 sib-pairs. We observed linkage of mean AAO to chromosome 21 in the whole sample (max LOD = 2.57). This came entirely from the NIMH sample (max LOD = 3.62), and was strongest in pairs with high mean AAO (>80). A similar effect was observed on chromosome 2q in the NIMH sample (max LOD = 2.73); this region was not typed in the IADC/UK sample. Suggestive evidence was observed in the combined sample of linkage of AAO difference to chromosome 19q (max LOD = 2.33) in the vicinity of APOE and 12p (max LOD = 2.22), with linkage strongest in sib-pairs with similar AAO. Mean ROD showed suggestive evidence of linkage to chromosome 9q in the whole sample (max LOD = 2.29), with the effect strongest in the NIMH sample (max LOD = 3.58), and in pairs with high mean ROD. Additional suggestive evidence was also observed in the NIMH sample with AAO difference on chromosome 6p (max LOD = 2.44) and 15p (max LOD = 1.87), with linkage strongest in pairs with similar AAO, and in the UK sample with mean ROD on chromosome 1p (max LOD = 2.73, linkage strongest in pairs with high mean ROD). We also observed suggestive evidence of increased identical by descent (IBD) in APOE epsilon4 homozygotes on chromosome 1 (max LOD = 3.08) and chromosome 9 (max LOD = 3.34). The previously reported genome-wide linkage of AD to chromosome 10 was not influenced by any of the covariates studied., (Copyright 2005 Wiley-Liss, Inc.)

Linkage studies indicate that the same region of chromosome 10 contains a risk locus for late onset Alzheimer disease (LOAD) and a QTL for plasma Abeta42 levels suggesting that a single locus may influence risk for AD by elevating plasma Abeta42 [Ertekin-Taner et al., 2000; Myers et al., 2000]. A strong positional and biological candidate is the urokinase-plasminogen activator (PLAU) gene. Eight polymorphisms spanning the entire gene were examined using case control (CC) and family-based association methods. No association was observed by any method making it unlikely that variation in PLAU explains our linkage data., (Copyright 2004 Wiley-Liss, Inc.)

This is an initial report on a six-site collaborative project, Genetics of Recurrent Early-Onset Depression (GenRED). This is a study of a large sample of families with recurrent major depressive disorder (DSM-IV) beginning by the age 30 in probands or 40 in relatives. Evidence suggests that early onset and recurrence of depressive episodes predict substantially increased risk of depression in first-degree relatives compared with the general population, suggesting that susceptibility genes might be mapped with this phenotype. The projected sample of 800-1,000 affected sibling pairs (ASPs) and other relatives will be studied using genome scan methods. Biological materials and blinded clinical data will be made available through the NIMH cell repository program. The sample should have good-to-excellent power to detect a locus associated with a 24% or greater population-wide increase in risk to siblings. We describe 838 affected individuals from the first 305 families containing 434 independent ASPs, or 613 ASPs counting all possible pairs. The mean age at the onset was 18.5 years, with a mean of 7.3 episodes and longest episode of 655 days. Almost all subjects had experienced at least 4 weeks of depression with five or more additional symptom criteria. Frequencies of symptoms and psychiatric and medical comorbid are provided. Substance use was more common in males, and panic disorder in females. Within pairs of affected siblings, correlations were significant for age at onset, substance abuse/dependence, panic disorder, obsessive-compulsive disorder and nicotine initiation and persistence. We replicated previously reported associations among comorbid panic disorder and social phobia, chronicity of depression and suicidal behavior. This suggests comparability of our cases to those in earlier large family studies. This dataset should prove useful for genetic studies of a highly familial form of major depressive disorder., (Copyright 2003 Wiley-Liss, Inc.)