Publications by authors named "Andrew Grupe"

24 Publications

  • Page 1 of 1

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

PLoS One 2021 28;16(4):e0243683. Epub 2021 Apr 28.

Department of Advanced Diagnostics, Quest Diagnostics, San Juan Capistrano, CA, United States of America.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0243683PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8081174PMC
September 2021

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

Biomed Res Int 2020 22;2020:3289023. Epub 2020 Jan 22.

Department of Genetics, Quest Diagnostics Nichols Institute, San Juan Capistrano, CA 92675, USA.

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 and (), 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 (23%), (23%), or the Lynch syndrome-associated genes (4%) and (2%). The other half were detected in 9 other genes: (17%) (15%), (4%), (4%), (2%), (2%), (2%), (2%), and (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.
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http://dx.doi.org/10.1155/2020/3289023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6998746PMC
November 2020

OncoKB: A Precision Oncology Knowledge Base.

JCO Precis Oncol 2017 Jul 16;2017. Epub 2017 May 16.

, Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Gastrointestinal Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Gynecologic Medical Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Breast Medicine Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Weill Cornell Medical College, New York, NY USA; , Breast Medicine Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Thoracic Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center , New York, NY, USA, Weill Cornell Medical College, New York, NY USA; , Head and Neck Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , , Department of Hematology and Oncology, Quest Diagnostics Nichols Institute, 33608 Ortega Highway, San Juan Capistrano, CA, 92675, USA; , Department of R&D and Bioinformatics, Quest Diagnostics Nichols Institute, 33608 Ortega Highway, San Juan Capistrano, CA, 92675, USA; , Head and Neck Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Weill Cornell Medical College, New York, NY USA; , Melanoma and Immunotherapeutics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Weill Cornell Medical College, New York, NY USA; , Gynecologic Medical Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Sarcoma Medical Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY, USA, Weill Cornell Medical College, New York, NY USA; Genitourinary Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Weill Cornell Medical College, New York, NY USA; , Developmental Therapeutics, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Sarcoma Medical Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY, USA, Weill Cornell Medical College, New York, NY USA; , Gastrointestinal Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Weill Cornell Medical College, New York, NY USA; , Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Department of Oncology and Internal Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Weill Cornell Medical College, New York, NY USA; , Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Genitourinary Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA , Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Developmental Therapeutics, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; , Breast Medicine Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Developmental Therapeutics, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Weill Cornell Medical College, New York, NY USA; , Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Genitourinary Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Weill Cornell Medical College, New York, NY USA; , Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA, Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

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.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5586540PMC
http://dx.doi.org/10.1200/PO.17.00011DOI Listing
July 2017

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

Mol Diagn Ther 2016 06;20(3):241-53

Department of Hematology and Oncology, Quest Diagnostics Nichols Institute, 33608 Ortega Highway, San Juan Capistrano, CA, 92675, USA.

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.
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http://dx.doi.org/10.1007/s40291-016-0197-0DOI Listing
June 2016

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

J Clin Endocrinol Metab 2013 Jun 17;98(6):E1122-30. Epub 2013 Apr 17.

University of Manchester, Manchester Academic Health Sciences Centre, Pediatric Endocrinology, Fifth Floor (Research), Royal Manchester Children's Hospital, Oxford Road, Manchester M13 9WL, United Kingdom.

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.
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http://dx.doi.org/10.1210/jc.2012-4283DOI Listing
June 2013

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

Alzheimers Dement 2010 Mar 18;6(2):118-24. Epub 2009 Sep 18.

Veterans Affairs Medical Center, Portland, OR, USA.

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.
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http://dx.doi.org/10.1016/j.jalz.2009.05.663DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3100774PMC
March 2010

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

Am J Med Genet B Neuropsychiatr Genet 2010 Jan;153B(1):235-42

Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.

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.
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http://dx.doi.org/10.1002/ajmg.b.30986DOI Listing
January 2010

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

PLoS One 2008 Jul 16;3(7):e2707. Epub 2008 Jul 16.

Celera, Alameda, California, United States of America.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0002707PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2442653PMC
July 2008

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

Pharmacogenomics 2007 Dec;8(12):1747-55

Celera, 1401 Harbor Bay Parkway, Alameda, CA 94502, USA.

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.
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http://dx.doi.org/10.2217/14622416.8.12.1747DOI Listing
December 2007

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

Hum Mol Genet 2008 Mar 6;17(5):759-67. Epub 2007 Dec 6.

Celera, 1401 Harbor Bay Parkway, Alameda, CA 94502, USA.

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.
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http://dx.doi.org/10.1093/hmg/ddm348DOI Listing
March 2008

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

Neurobiol Dis 2008 Feb 16;29(2):293-6. Epub 2007 Sep 16.

Celera, 1401 Harbor Bay Parkway, Alameda, CA, USA.

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.
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http://dx.doi.org/10.1016/j.nbd.2007.09.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2323581PMC
February 2008

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

Mol Neurodegener 2007 Apr 12;2. Epub 2007 Apr 12.

Department of Neurology, Washington University, St, Louis, MO, USA.

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.
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http://dx.doi.org/10.1186/1750-1326-2-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1857699PMC
April 2007

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

Hum Mol Genet 2007 Apr 22;16(8):865-73. Epub 2007 Feb 22.

Celera Diagnostics, 1401 Harbor Bay Parkway, Alameda, CA 94502, USA.

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).
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http://dx.doi.org/10.1093/hmg/ddm031DOI Listing
April 2007

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

Hum Mutat 2006 Oct;27(10):1017-23

Celera Diagnostics, Alameda, California 94502, USA.

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.
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http://dx.doi.org/10.1002/humu.20382DOI Listing
October 2006

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

Hum Mol Genet 2006 Sep 17;15(17):2560-8. Epub 2006 Jul 17.

Celera Diagnostics, Alameda, CA 94502, USA.

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.
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http://dx.doi.org/10.1093/hmg/ddl178DOI Listing
September 2006

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

Am J Hum Genet 2006 Jan 15;78(1):78-88. Epub 2005 Nov 15.

Celera Diagnostics, Alameda, CA, USA.

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.
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http://dx.doi.org/10.1086/498851DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1380225PMC
January 2006

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

Ann Neurol 2006 Jan;59(1):21-6

Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Street, St. Louis, MO 63110, USA.

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.
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http://dx.doi.org/10.1002/ana.20673DOI Listing
January 2006

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

Am J Med Genet B Neuropsychiatr Genet 2005 Jul;136B(1):62-8

Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA.

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.
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http://dx.doi.org/10.1002/ajmg.b.30186DOI Listing
July 2005

Genetic association of the APP binding protein 2 gene (APBB2) with late onset Alzheimer disease.

Hum Mutat 2005 Mar;25(3):270-7

Celera Diagnostics, Alameda, California 94502, USA.

Alzheimer disease (AD) is a complex neurodegenerative disorder predisposed by multiple genetic factors. Mutations in amyloid beta precursor protein (APP) are known to be associated with autosomal dominant, early onset familial AD and possibly also late onset AD (LOAD). A number of genes encoding proteins capable of binding to APP have been identified, but their contribution to AD pathobiology remains unclear. Conceivably, mutations in these genes may play a role in affecting AD susceptibility, which appears to be substantiated by some genetic studies. Here we report results of the first genetic association study with APBB2, an APP binding protein (also known as FE65L), and LOAD, in three independently collected case-control series totaling approximately 2,000 samples. Two SNPs were significantly associated with LOAD in two sample series and in meta-analyses of all three sample sets (for rs13133980: odds ratio [OR](hom)=1.36 [95% CI: 1.05-1.75], OR(het)=1.32 [95% CI: 1.04-1.67], minor allele frequency=43%, P=0.041; and for hCV1558625: OR(hom)=1.37 [95% CI: 1.06-1.77], OR(het)=1.02 [95% CI: 0.82-1.26], minor allele frequency=48%, P=0.026). One of these SNPs, located in a region conserved between the human and mouse genome, showed a significant interaction with age of disease onset. For this marker, the association with LOAD was most pronounced in subjects with disease onset before 75 years of age (OR(hom)=2.43 [95% CI: 1.61-3.67]; OR(het)=2.15 [95% CI: 1.46-3.17]; P=0.00006) in the combined sample set. Our data raise the possibility that genetic variations in APBB2 may affect LOAD susceptibility.
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http://dx.doi.org/10.1002/humu.20138DOI Listing
March 2005

Association of late-onset Alzheimer's disease with genetic variation in multiple members of the GAPD gene family.

Proc Natl Acad Sci U S A 2004 Nov 26;101(44):15688-93. Epub 2004 Oct 26.

Celera Diagnostics, Alameda, CA 94502, USA.

Although several genes have been implicated in the development of the early-onset autosomal dominant form of Alzheimer's disease (AD), the genetics of late-onset AD (LOAD) is complex. Loci on several chromosomes have been linked to the disease, but so far only the apolipoprotein E gene has been consistently shown to be a risk factor. We have performed a large-scale single-nucleotide polymorphism (SNP)-based association study, across the region of linkage on chromosome 12, in multiple case-control series totaling 1,089 LOAD patients and 1,196 control subjects and report association with SNPs in the glyceraldehyde-3-phosphate dehydrogenase (GAPD) gene. Subsequent analysis of GAPD paralogs on other chromosomes demonstrated association with two other paralogs. A significant association between LOAD and a compound genotype of the three GAPD genes was observed in all three sample sets. Individually, these SNPs make differential contributions to disease risk in each of the casecontrol series, suggesting that variants in functionally similar genes may account for series-to-series heterogeneity of disease risk. Our observations raise the possibility that GAPD genes are AD risk factors, a hypothesis that is consistent with the role of GAPD in neuronal apoptosis.
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http://dx.doi.org/10.1073/pnas.0403535101DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC524264PMC
November 2004

Association of ABCA1 with late-onset Alzheimer's disease is not observed in a case-control study.

Neurosci Lett 2004 Aug;366(3):268-71

Celera Diagnostics, Alameda, CA, USA.

Genetic association of ABCA1 or the ATP-binding cassette A1 transporter with late-onset Alzheimer's disease (LOAD) has recently been proposed for a haplotype comprised of three single nucleotide polymorphisms (SNPs). We have genotyped these and other ABCA1 SNPs in a LOAD case-control series of 796 individuals (419 cases versus 377 controls) collected at Washington University. While our sample series is larger and thus presumably has greater power than any of the series used to implicate ABCA1, we were unable to replicate the published association, using either single markers or multiple marker haplotypes. Further, we did not observe significant and replicated association of other ABCA1 SNPs we examined with the disease, thus these ABCA1 variants do not appear to influence the risk of LOAD in this study.
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http://dx.doi.org/10.1016/j.neulet.2004.05.047DOI Listing
August 2004

Alpha-T-catenin is expressed in human brain and interacts with the Wnt signaling pathway but is not responsible for linkage to chromosome 10 in Alzheimer's disease.

Neuromolecular Med 2004 ;5(2):133-46

Department of Neuroscience, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, United Kingdom.

The gene encoding alpha-T-catenin, CTNNA3, is positioned within a region on chromosome 10, showing strong evidence of linkage to Alzheimer's disease (AD), and is therefore a good positional candidate gene for this disorder. We have demonstrated that alpha-T-catenin is expressed in human brain, and like other alpha-catenins, it inhibits Wnt signaling and is therefore also a functional candidate. We initially genotyped two single-nucleotide polymorphisms (SNPs) in the gene, in four independent samples comprising over 1200 cases and controls but failed to detect an association with either SNP. Similarly, we found no evidence for association between CTNNA3 and AD in a sample of subjects showing linkage to chromosome 10, nor were these SNPs associated with Abeta deposition in brain. To comprehensively screen the gene, we genotyped 30 additional SNPs in a subset of the cases and controls (n > 700). None of these SNPs was associated with disease. Although an excellent candidate, we conclude that CTNNA3 is unlikely to account for the AD susceptibility locus on chromosome 10.
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http://dx.doi.org/10.1385/NMM:5:2:133DOI Listing
July 2004

A polymorphism in the TCF7 gene, C883A, is associated with type 1 diabetes.

Diabetes 2003 Jun;52(6):1579-82

Children's Hospital Oakland Research Institute, 5700 Martin Luther King Jr. Way, Oakland, CA 94609, USA.

Type 1 diabetes is an autoimmune disease with a Th1 phenotype in which insulin-producing beta-cells in the pancreas are destroyed. The T-cell-specific transcription factor TCF7 activates genes involved in immune regulation and is a candidate locus for genetic susceptibility to type 1 diabetes. A nonsynonymous single nucleotide polymorphism (SNP) (Pro to Thr) in the TCF7 gene, C883A, was examined in samples from 282 Caucasian multiplex type 1 diabetic families. HLA-DRB1 and -DQB1 genotypes were previously determined for these samples, allowing data stratification based on HLA-associated risk. The transmission disequilibrium test showed significant overtransmission of the A allele from fathers (64.1%, P < 0.007) and nonsignificant overtransmission (57.4%, P < 0.06) of the A allele to patients who do not carry the highest-risk HLA-DR3/DR4 genotype. Elliptical sib pair analysis showed significant associations of the A allele with type 1 diabetes in paternal transmissions (P < 0.03), transmissions to male children (P < 0.04), and in the non-DR3/DR4 group (P < 0.04). These data also suggest that TCF7 C883A may affect age of disease onset. Analysis of genotype data from surrounding SNPs suggests that this TCF7 polymorphism may itself represent a risk factor for type 1 diabetes.
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http://dx.doi.org/10.2337/diabetes.52.6.1579DOI Listing
June 2003
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