Cited by 154Genetic Associations and EpidemiologyGenomics and Rare DiseasesGenetic Mapping and Diversity in Plants and Animals

Screening a large reference sample to identify very low frequency sequence variants: comparisons between two genes

Glatt, Charles E., DeYoung, Joseph A., Delgado, Sharon, Service, Susan K., Giacomini, Kathleen M., Edwards, Robert H., Risch, Neil, Freimer, Nelson B.·2001·Nature Genetics

Abstract

Most human sequence variation is in the form of single-nucleotide polymorphisms (SNPs). It has been proposed that coding-region SNPs (cSNPs) be used for direct association studies to determine the genetic basis of complex traits. The success of such studies depends on the frequency of disease-associated alleles, and their distribution in different ethnic populations. If disease-associated alleles are frequent in most populations, then direct genotyping of candidate variants could show robust associations in manageable study samples. This approach is less feasible if the genetic risk from a given candidate gene is due to many infrequent alleles. Previous studies of several genes demonstrated that most variants are relatively infrequent (<0.05). These surveys genotyped small samples (n<75) and thus had limited ability to identify rare alleles. Here we evaluate the prevalence and distribution of such rare alleles by genotyping an ethnically diverse reference sample that is more than six times larger than those used in previous studies (n=450). We screened for variants in the complete coding sequence and intron-exon junctions of two candidate genes for neuropsychiatric phenotypes: SLC6A4, encoding the serotonin transporter; and SLC18A2, encoding the vesicular monoamine transporter. Both genes have unique roles in neuronal transmission, and variants in either gene might be associated with neurobehavioral phenotypes.

Integrity signals

Registry

Crossref · 10.1038/86948

Cites

18 of 18 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Glatt, C. E., DeYoung, J. A., Delgado, S., Service, S. K., Giacomini, K. M., Edwards, R. H., Risch, N., & Freimer, N. B.
Affiliations
  • University of California, San Francisco (US)
  • Stanford Medicine (US)
Corresponding author
Freimer, Nelson B.
Venue
Nature Genetics
Published
2001-04
Volume
27
Issue
4
Pages
435-438
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
OpenAlex
W1568552337
Cited by
154
References
18
Citations by year
2025: 1 · 2023: 2 · 2022: 2 · 2021: 2 · 2020: 4 · 2019: 4 · 2018: 2 · 2016: 1 · 2015: 1 · 2014: 3 · 2013: 7 · 2012: 4
FWCI
9.65
Type
journal article
Language
en
Open access
closed
Locations
  • Nature Genetics (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institute of Mental Health (K02MH001375, MH49499, MH01375, R01MH049499)
  • National Institute of General Medical Sciences (GM61390)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords
rare variants, single nucleotide polymorphisms, serotonin transporter, vesicular monoamine transporter 2, vesicular monoamine transporter, neuropsychiatric phenotypes, genetic association studies, allele frequency, complex traits
MeSH terms
Alleles, Gene Frequency, Genetic Testing, Humans, Molecular Sequence Data, Polymerase Chain Reaction, DNA Primers, Polymorphism, Single Nucleotide

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review