Development and validation of a high throughput SARS-CoV-2 whole genome sequencing workflow in a clinical laboratory.

Monitoring new mutations in SARS-CoV-2 provides crucial information for identifying diagnostic and therapeutic targets and important insights to achieve a more effective COVID-19 control strategy. Next generation sequencing (NGS) technologies have been widely used for whole genome sequencing (WGS) of SARS-CoV-2. While various NGS methods have been reported, one chief limitation has been the complexity of the workflow, limiting the scalability. Here, we overcome this limitation by designing a laboratory workflow optimized for high-throughput studies. The workflow utilizes modified ARTIC network v3 primers for SARS-CoV-2 whole genome amplification. NGS libraries were prepared by a 2-step PCR method, similar to a previously reported tailed PCR method, with further optimizations to improve amplicon balance, to minimize amplicon dropout for viral genomes harboring primer-binding site mutation(s), and to integrate robotic liquid handlers. Validation studies demonstrated that the optimized workflow can process up to 2688 samples in a single sequencing run without compromising sensitivity and accuracy and with fewer amplicon dropout events compared to the standard ARTIC protocol. We additionally report results for over 65,000 SARS-CoV-2 whole genome sequences from clinical specimens collected in the United States between January and September of 2021, as part of an ongoing national genomics surveillance effort.

Analytical validation and performance characteristics of a 48-gene next-generation sequencing panel for detecting potentially actionable genomic alterations in myeloid neoplasms.

Identification of genomic mutations by molecular testing plays an important role in diagnosis, prognosis, and treatment of myeloid neoplasms. Next-generation sequencing (NGS) is an efficient method for simultaneous detection of clinically significant genomic mutations with high sensitivity. Various NGS based in-house developed and commercial myeloid neoplasm panels have been integrated into routine clinical practice. However, some genes frequently mutated in myeloid malignancies are particularly difficult to sequence with NGS panels (e.g., CEBPA, CARL, and FLT3). We report development and validation of a 48-gene NGS panel that includes genes that are technically challenging for molecular profiling of myeloid neoplasms including acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasms (MPN). Target regions were captured by hybridization with complementary biotinylated DNA baits, and NGS was performed on an Illumina NextSeq500 instrument. A bioinformatics pipeline that was developed in-house was used to detect single nucleotide variations (SNVs), insertions/deletions (indels), and FLT3 internal tandem duplications (FLT3-ITD). An analytical validation study was performed on 184 unique specimens for variants with allele frequencies ≥5%. Variants identified by the 48-gene panel were compared to those identified by a 35-gene hematologic neoplasms panel using an additional 137 unique specimens. The developed assay was applied to a large cohort (n = 2,053) of patients with suspected myeloid neoplasms. Analytical validation yielded 99.6% sensitivity (95% CI: 98.9-99.9%) and 100% specificity (95% CI: 100%). Concordance of variants detected by the 2 tested panels was 100%. Among patients with suspected myeloid neoplasms (n = 2,053), 54.5% patients harbored at least one clinically significant mutation: 77% in AML patients, 48% in MDS, and 45% in MPN. Together, these findings demonstrate that the assay can identify mutations associated with diagnosis, prognosis, and treatment options of myeloid neoplasms even in technically challenging genes.

Development and Validation of a 34-Gene Inherited Cancer Predisposition Panel Using Next-Generation Sequencing.

The use of genetic testing to identify individuals with hereditary cancer syndromes has been widely adopted by clinicians for management of inherited cancer risk. The objective of this study was to develop and validate a 34-gene inherited cancer predisposition panel using targeted capture-based next-generation sequencing (NGS). The panel incorporates genes underlying well-characterized cancer syndromes, such as BRCA1 and BRCA2 (BRCA1/2), along with more recently discovered genes associated with increased cancer risk. We performed a validation study on 133 unique specimens, including 33 with known variant status; known variants included single nucleotide variants (SNVs) and small insertions and deletions (Indels), as well as copy-number variants (CNVs). The analytical validation study achieved 100% sensitivity and specificity for SNVs and small Indels, with 100% sensitivity and 98.0% specificity for CNVs using in-house developed CNV flagging algorithm. We employed a microarray comparative genomic hybridization (aCGH) method for all specimens that the algorithm flags as CNV-positive for confirmation. In combination with aCGH confirmation, CNV detection specificity improved to 100%. We additionally report results of the first 500 consecutive specimens submitted for clinical testing with the 34-gene panel, identifying 53 deleterious variants in 13 genes in 49 individuals. Half of the detected pathogenic/likely pathogenic variants were found in BRCA1 (23%), BRCA2 (23%), or the Lynch syndrome-associated genes PMS2 (4%) and MLH1 (2%). The other half were detected in 9 other genes: MUTYH (17%), CHEK2 (15%), ATM (4%), PALB2 (4%), BARD1 (2%), CDH1 (2%), CDKN2A (2%), RAD51C (2%), and RET (2%). Our validation studies and initial clinical data demonstrate that a 34-gene inherited cancer predisposition panel can provide clinically significant information for cancer risk assessment.

OncoKB: A Precision Oncology Knowledge Base.

PURPOSE: With prospective clinical sequencing of tumors emerging as a mainstay in cancer care, there is an urgent need for a clinical support tool that distills the clinical implications associated with specific mutation events into a standardized and easily interpretable format. To this end, we developed OncoKB, an expert-guided precision oncology knowledge base. METHODS: OncoKB annotates the biological and oncogenic effect and the prognostic and predictive significance of somatic molecular alterations. Potential treatment implications are stratified by the level of evidence that a specific molecular alteration is predictive of drug response based on US Food and Drug Administration (FDA) labeling, National Comprehensive Cancer Network (NCCN) guidelines, disease-focused expert group recommendations and the scientific literature. RESULTS: To date, over 3000 unique mutations, fusions, and copy number alterations in 418 cancer-associated genes have been annotated. To test the utility of OncoKB, we annotated all genomic events in 5983 primary tumor samples in 19 cancer types. Forty-one percent of samples harbored at least one potentially actionable alteration, of which 7.5% were predictive of clinical benefit from a standard treatment. OncoKB annotations are available through a public web resource (http://oncokb.org/) and are also incorporated into the cBioPortal for Cancer Genomics to facilitate the interpretation of genomic alterations by physicians and researchers. CONCLUSION: OncoKB, a comprehensive and curated precision oncology knowledge base, offers oncologists detailed, evidence-based information about individual somatic mutations and structural alterations present in patient tumors with the goal of supporting optimal treatment decisions.

Mutation Yield of a 34-Gene Solid Tumor Panel in Community-Based Tumor Samples.

BACKGROUND: Several targeted therapies have been approved for treatment of solid tumors. Identification of gene mutations that indicate response to these therapies is rapidly progressing. A 34-gene next-generation sequencing (NGS) panel, developed and validated by us, was evaluated to detect additional mutations in community-based cancer specimens initially sent to our reference laboratory for routine molecular testing. METHODS: Consecutive de-identified clinical specimens (n = 121) from melanoma cases (n = 31), lung cancer cases (n = 27), colorectal cancer cases (n = 33), and breast cancer cases (n = 30) were profiled by NGS, and the results were compared with routine molecular testing. RESULTS: Upon initial mutation testing, 20 % (24/121) were positive. NGS detected ≥1 additional mutation not identified by routine testing in 74 % of specimens (90/121). Of the specimens with additional mutations, 16 harbored mutations in National Comprehensive Cancer Network guideline genes. These various additional mutations were in gene regions not routinely covered, in genes not routinely tested, and/or present at low allele frequencies. Moreover, NGS yielded no false negatives. Overall, NGS detected mutations in 59 % of the genes (20/34) included in the panel, 75 % of which (15/20) were detected in multiple tumor types. Mutations in TP53 were found in 51 % of tumors tested (62/121). Mutations in at least one other (non-TP53) gene present in the panel were detected in 64 % of cases (77/121). CONCLUSION: This assay provides improved breadth and sensitivity for profiling clinically relevant genes in these prevalent solid tumor types.

Characterizing short stature by insulin-like growth factor axis status and genetic associations: results from the prospective, cross-sectional, epidemiogenetic EPIGROW study.

CONTEXT: Serum IGF-I levels are often low in patients with short stature (SS) without defined etiology. Hence, genetic investigations have focused on the GH-IGF-I axis. OBJECTIVE: Our objectives were to characterize IGF-I axis status and search for a broader range of genetic associations in children with SS and normal GH. DESIGN AND SETTING: We conducted a prospective, cross-sectional, epidemiogenetic case-control study in 9 European countries (2008-2010). PARTICIPANTS: Children (n = 275) aged ≥2 years with SS without defined etiology (≤-2.5 height SD score [SDS]) and ≥1 peak GH ≥7 µg/L) were recruited. METHODS: Serum IGF-I, IGF-binding protein-3 (IGFBP-3), and acid-labile subunit (ALS) levels were measured in a central laboratory. Candidate gene exome sequencing was performed in this cohort and ethnicity-matched controls. RESULTS: Serum IGF-I, IGFBP-3, and ALS levels were highly correlated, but there was a discrepancy between prevalence of IGF-I, IGFBP-3, and ALS deficiencies (53%, 30%, and 0.8%, respectively). An insertion-deletion (Indel) on the IGF1 gene (P = 1.2 × 10(-5), Bonferroni-corrected; case vs control frequency: 0.04 vs 0.112), an Indel on NFKB1 (P = 1.36 × 10(-10); case vs control frequency: 0.464 vs 0.272), and 2 single-nucleotide polymorphisms on ZBTB38 (P < 2.3 × 10(-6)) were associated with SS. At P < 10(-4), single-nucleotide polymorphisms on genes related to protein kinase regulation, MAPK, and Fanconi pathways were also associated with SS. CONCLUSIONS: IGF-I deficiency is a common feature in SS without defined etiology; an Indel in the IGF1 gene was associated with SS. However, genes involved in transcriptional regulation (NFKB1 and ZBTB38) and growth factor signaling were also associated, providing further candidates for genetic investigations on individual patients.

The FAS gene, brain volume, and disease progression in Alzheimer's disease.

OBJECTIVE: We sought to identify single-nucleotide polymorphisms (SNPs) associated with Alzheimer's disease (AD) progression and brain volume. METHODS: Ninety-seven SNPs were genotyped in 243 subjects from a longitudinal study of healthy aging. Subjects who received a diagnosis of cognitive impairment (CI) at any study visit (before their most recent visit) and had DNA in the study's DNA bank were included. Progression of AD was defined as the duration from onset of CI to diagnosis of AD. Association of each of the 97 SNPs with AD progression was tested via Cox model. Those SNPs meeting a criterion of nominal significance (P < 0.05) for association with AD progression were reassessed to account for multiple testing by repeating the marker selection process in 10,000 random permutations. Next, the association between the one SNP that survived the multiple-testing adjustment and brain volume was determined by multiple regression analysis in a subgroup of subjects for whom magnetic-resonance imaging (MRI)-derived brain-volume data were available. Brain volumes were adjusted for age at MRI, gender, and time from MRI to onset of CI. RESULTS: The minor allele of rs1468063 in the FAS gene, which is member 6 of the tumor necrosis factor receptor superfamily, was significantly associated with faster AD progression after adjustment for multiple testing (P(permutation) = 0.049). The same allele in rs1468063 was associated with smaller brain volumes and larger ventricular volumes (P = 0.02 and 0.04, respectively). CONCLUSIONS: The FAS gene, which plays a role in apoptosis, may be associated with AD by modulating the apoptosis and neuronal loss secondary to AD neuropathology.

Sexually dimorphic effect of the Val66Met polymorphism of BDNF on susceptibility to Alzheimer's disease: New data and meta-analysis.

Conflicting results have been reported as to whether genetic variations (Val66Met and C270T) of the brain-derived neurotrophic factor gene (BDNF) confer susceptibility to Alzheimer's disease (AD). We genotyped these polymorphisms in a Japanese sample of 657 patients with AD and 525 controls, and obtained weak evidence of association for Val66Met (P = 0.063), but not for C270T. After stratification by sex, we found a significant allelic association between Val66Met and AD in women (P = 0.017), but not in men. To confirm these observations, we collected genotyping data for each sex from 16 research centers worldwide (4,711 patients and 4,537 controls in total). The meta-analysis revealed that there was a clear sex difference in the allelic association; the Met66 allele confers susceptibility to AD in women (odds ratio = 1.14, 95% CI 1.05-1.24, P = 0.002), but not in men. Our results provide evidence that the Met66 allele of BDNF has a sexually dimorphic effect on susceptibility to AD.

Neither replication nor simulation supports a role for the axon guidance pathway in the genetics of Parkinson's disease.

Susceptibility to sporadic Parkinson's disease (PD) is thought to be influenced by both genetic and environmental factors and their interaction with each other. Statistical models including multiple variants in axon guidance pathway genes have recently been purported to be capable of predicting PD risk, survival free of the disease and age at disease onset; however the specific models have not undergone independent validation. Here we tested the best proposed risk panel of 23 single nucleotide polymorphisms (SNPs) in two PD sample sets, with a total of 525 cases and 518 controls. By single marker analysis, only one marker was significantly associated with PD risk in one of our sample sets (rs6692804: P = 0.03). Multi-marker analysis using the reported model found a mild association in one sample set (two sided P = 0.049, odds ratio for each score change = 1.07) but no significance in the other (two sided P = 0.98, odds ratio = 1), a stark contrast to the reported strong association with PD risk (P = 4.64x10(-38), odds ratio as high as 90.8). Following a procedure similar to that used to build the reported model, simulated multi-marker models containing SNPs from randomly chosen genes in a genome wide PD dataset produced P-values that were highly significant and indistinguishable from similar models where disease status was permuted (3.13x10(-23) to 4.90x10(-64)), demonstrating the potential for overfitting in the model building process. Together, these results challenge the robustness of the reported panel of genetic markers to predict PD risk in particular and a role of the axon guidance pathway in PD genetics in general.

SORL1 variants and risk of late-onset Alzheimer's disease.

A recent study reported significant association of late-onset Alzheimer's disease (LOAD) with multiple single nucleotide polymorphisms (SNPs) and haplotypes in SORL1, a neuronal sortilin-related receptor protein known to be involved in the trafficking and processing of amyloid precursor protein. Here we attempted to validate this finding in three large, well characterized case-control series. Approximately 2000 samples from the three series were individually genotyped for 12 SNPs, including the 10 reported significant SNPs and 2 that constitute the reported significant haplotypes. A total of 25 allelic and haplotypic association tests were performed. One SNP rs2070045 was marginally replicated in the three sample sets combined (nominal P=0.035); however, this result does not remain significant when accounting for multiple comparisons. Further validation in other sample sets will be required to assess the true effects of SORL1 variants in LOAD.

Evidence that common variation in NEDD9 is associated with susceptibility to late-onset Alzheimer's and Parkinson's disease.

Late-onset Alzheimer's disease (LOAD) and Parkinson's disease (PD) are the most common neurodegenerative disorders and in both diseases susceptibility is known to be influenced by genes. We set out to identify novel susceptibility genes for LOAD by performing a large scale, multi-tiered association study testing 4692 single nucleotide polymorphism (SNPs). We identified a SNP within a putative transcription factor binding site in the NEDD9 gene (neural precursor cell expressed, developmentally down-regulated), that shows good evidence of association with disease risk in four out of five LOAD samples [N = 3521, P = 5.38x10(-6), odds ratio (OR) = 1.38 (1.20-1.59)] and in addition, we observed a similar pattern of association in two PD sample sets [N = 1464, P = 0.0145, OR =1.31 (1.05-1.62)]. In exploring a potential mechanism for the association, we observed that expression of NEDD9 and APOE show a strong inverse correlation in the hippocampus of Alzheimer's cases. These data implicate NEDD9 as a novel susceptibility gene for LOAD and possibly PD.

Genetics of late-onset Alzheimer's disease: progress and prospect.

Genetic susceptibility factors for late-onset Alzheimer's disease remain largely elusive, with the exception of apolipoprotein E4 (APOE e4) as the only confirmed genetic risk factor. Numerous other putative risk markers have been proposed, although all suffer inconsistent replication. These results suggest that modest effect sizes are likely to be the norm for non-APOE-related factors. This unsettling situation has been similar to other complex diseases such as diabetes and cardiovascular diseases until very recently, when a spate of new, although weak, genetic markers has been convincingly linked to these conditions. If we assume that multiple weak factors, together with APOE e4, account for the genetic contribution to late-onset Alzheimer's disease risk, it will require the concerted efforts of the greater Alzheimer's genetics community to pool existing genetic resources and/or data to identify novel genetic risk factors that are genuine. Increased confidence in the disease-associated factors will provide the foundation to develop better diagnostic and prognostic tests, select new drug targets and, perhaps, elucidate pharmacogenetic markers that assist in making the best treatment decisions.

Apolipoprotein E levels in cerebrospinal fluid and the effects of ABCA1 polymorphisms.

BACKGROUND: Animal studies suggest that brain apolipoprotein E (apoE) levels influence amyloid-beta (Abeta) deposition and thus risk for Alzheimer's disease (AD). We have previously demonstrated that deletion of the ATP-binding cassette A1 transporter (ABCA1) in mice causes dramatic reductions in brain and cerebrospinal fluid (CSF) apoE levels and lipidation. To examine whether polymorphisms in ABCA1 affect CSF apoE levels in humans, we measured apoE in CSF taken from 168 subjects who were 43 to 91 years old and were either cognitively normal or who had mild AD. We then genotyped the subjects for ten previously identified ABCA1 single nucleotide polymorphisms (SNPs). RESULTS: In all subjects, the mean CSF apoE level was 9.09 microg/ml with a standard deviation of 2.70 microg/ml. Levels of apoE in CSF samples taken from the same individual two weeks apart were strongly correlated (r2 = 0.93, p < 0.01). In contrast, CSF apoE levels in different individuals varied widely (coefficient of variation = 46%). CSF apoE levels did not vary according to AD status, APOE genotype, gender or race. Average apoE levels increased with age by approximately 0.5 microg/ml per 10 years (r2 = 0.05, p = 0.003). We found no significant associations between CSF apoE levels and the ten ABCA1 SNPs we genotyped. Moreover, in a separate sample of 1225 AD cases and 1431 controls, we found no association between the ABCA1 SNP rs2230806 and AD as has been previously reported. CONCLUSION: We found that CSF apoE levels vary widely between individuals, but are stable within individuals over a two-week interval. AD status, APOE genotype, gender and race do not affect CSF apoE levels, but average CSF apoE levels increase with age. Given the lack of association between CSF apoE levels and genotypes for the ABCA1 SNPs we examined, either these SNPs do not affect ABCA1 function or if they do, they do not have strong effects in the CNS. Finally, we find no evidence for an association between the ABCA1 SNP rs2230806 and AD in a large sample set.

Evidence for novel susceptibility genes for late-onset Alzheimer's disease from a genome-wide association study of putative functional variants.

This study sets out to identify novel susceptibility genes for late-onset Alzheimer's disease (LOAD) in a powerful set of samples from the UK and USA (1808 LOAD cases and 2062 controls). Allele frequencies of 17 343 gene-based putative functional single nucleotide polymorphisms (SNPs) were tested for association with LOAD in a discovery case-control sample from the UK. A tiered strategy was used to follow-up significant variants from the discovery sample in four independent sample sets. Here, we report the identification of several candidate SNPs that show significant association with LOAD. Three of the identified markers are located on chromosome 19 (meta-analysis: full sample P = 6.94E - 81 to 0.0001), close to the APOE gene and exhibit linkage disequilibrium (LD) with the APOEepsilon4 and epsilon2/3 variants (0.09 < D'<1). Two of the three SNPs can be regarded as study-wide significant (expected number of false positives reaching the observed significance level less than 0.05 per study). Sixteen additional SNPs show evidence for association with LOAD [P = 0.0010-0.00006; odds ratio (OR) = 1.07-1.45], several of which map to known linkage regions, biological candidate genes and novel genes. Four SNPs not in LD with APOE show a false positive rate of less than 2 per study, one of which shows study-wide suggestive evidence taking account of 17 343 tests. This is a missense mutation in the galanin-like peptide precursor gene (P = 0.00005, OR = 1.2, false positive rate = 0.87).

Genetic evidence for ubiquitin-specific proteases USP24 and USP40 as candidate genes for late-onset Parkinson disease.

Linkage studies have defined susceptibility regions for late-onset Parkinson disease (PD) on chromosomes 1 and 2, but specific genetic variants have not been definitively identified. Here we report the results of a case-control study to identify disease-associated single nucleotide polymorphisms (SNPs) in these loci. In the initial phase of our study, we genotyped two putative functional SNPs in ubiquitin-specific protease 24 (USP24), a biological candidate gene within the chromosome 1 linkage region, and scanned the chromosome 2 linkage peak with 43 SNPs in a sample set of 224 PD cases and 186 matched controls. Both USP24 SNPs were significantly associated with disease risk (p = 0.0037 for rs1165222:T > C, p.Thr195ILe, and p = 0.037 for rs13312:C > G, a SNP in the 3'-untranslated region), and one marker, rs1048603:C > T, p.Arg1123Cys, in USP40 was significant from the chromosome 2 scan (p = 0.038). Further genotyping of the region surrounding these initial markers led us to identify 19 additional SNPs with strong disease association. In the second phase, we genotyped the 22 significant markers in an additional 110 cases and 162 controls, which together with part of the initial sample set (201 cases and 149 controls) constitute an expanded sample set of 311 age- and gender-matched case-control pairs. Twenty-one markers were significant in the expanded sample set (most significant allelic p-value: 0.0006 for rs287235:C > G on chromosome 1, and 0.005 for rs838552:T > C on chromosome 2), and six SNPs in USP24 remained significant after conservatively adjusting for testing 27 markers (pBonferroni = 0.017-0.049). It is unlikely that population stratification contributed to this finding, as population stratification was undetectable in our sample set using 78 null markers. Our data suggest that genetic variants in USP24 and USP40 affect the risk for late-onset PD, which is consistent with the predicted role of the ubiquitination pathway in PD etiology.

DAPK1 variants are associated with Alzheimer's disease and allele-specific expression.

Genetic factors play an important role in the etiology of late-onset Alzheimer's disease (LOAD). We tested gene-centric single nucleotide polymorphisms (SNPs) on chromosome 9 and identified two SNPs in the death-associated protein kinase, DAPK1, that show significant association with LOAD. SNP rs4878104 was significantly associated with LOAD in our discovery case-control sample set (WU) and replicated in each of two initial validation case-control sample sets (P<0.05, UK1, SD). The risk-allele frequency of this SNP showed a similar direction in three other case-control sample sets. A meta-analysis of the six sample sets combined, totaling 2012 cases and 2336 controls, showed an allelic P-value of 0.0016 and an odds ratio (OR) of 0.87 (95%CI: 0.79-0.95). Minor allele homozygotes had a consistently lower risk than major allele homozygotes in the discovery and initial two replication sample sets, which remained significant in the meta-analysis of all six sample sets (OR=0.7, 95%CI: 0.58-0.85), whereas the risk for heterozygous subjects was not significantly different from that of major allele homozygotes. A second SNP, rs4877365, which is in high linkage disequilibrium with rs4878104 (r2=0.64), was also significantly associated with LOAD (meta P=0.0017 in the initial three sample sets). Furthermore, DAPK1 transcripts show differential allelic gene expression, and both rs4878104 and rs4877365 were significantly associated with DAPK1 allele-specific expression (P=0.015 to <0.0001). These data suggest that genetic variation in DAPK1 modulates susceptibility to LOAD.

A scan of chromosome 10 identifies a novel locus showing strong association with late-onset Alzheimer disease.

Strong evidence of linkage to late-onset Alzheimer disease (LOAD) has been observed on chromosome 10, which implicates a wide region and at least one disease-susceptibility locus. Although significant associations with several biological candidate genes on chromosome 10 have been reported, these findings have not been consistently replicated, and they remain controversial. We performed a chromosome 10-specific association study with 1,412 gene-based single-nucleotide polymorphisms (SNPs), to identify susceptibility genes for developing LOAD. The scan included SNPs in 677 of 1,270 known or predicted genes; each gene contained one or more markers, about half (48%) of which represented putative functional mutations. In general, the initial testing was performed in a white case-control sample from the St. Louis area, with 419 LOAD cases and 377 age-matched controls. Markers that showed significant association in the exploratory analysis were followed up in several other white case-control sample sets to confirm the initial association. Of the 1,397 markers tested in the exploratory sample, 69 reached significance (P < .05). Five of these markers replicated at P < .05 in the validation sample sets. One marker, rs498055, located in a gene homologous to RPS3A (LOC439999), was significantly associated with Alzheimer disease in four of six case-control series, with an allelic P value of .0001 for a meta-analysis of all six samples. One of the case-control samples with significant association to rs498055 was derived from the linkage sample (P = .0165). These results indicate that variants in the RPS3A homologue are associated with LOAD and implicate this gene, adjacent genes, or other functional variants (e.g., noncoding RNAs) in the pathogenesis of this disorder.

Ubiquilin 1 polymorphisms are not associated with late-onset Alzheimer's disease.

Several studies have reported evidence for linkage of late-onset Alzheimer's disease (LOAD) to chromosome 9. Recently, an intronic polymorphism affecting alternative splicing of exon 8 of ubiquilin 1 (UBQLN1) was reported to be associated with LOAD. We attempted to replicate this observation by genotyping this polymorphism, rs12344615 (also known as UBQ-8i), in a large sample of 1,544 LOAD cases and 1,642 nondemented controls. We did not find any evidence that this single nucleotide polymorphism, or any of six others tested in UBQLN1, increases risk for LOAD.

Association studies between risk for late-onset Alzheimer's disease and variants in insulin degrading enzyme.

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_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.