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CDRH: A Database of Complex Disease-related Haplotypes in Human
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Table 2 The statistical information of the top six complex diseases in the CDRH database
Disease name
Haplotypes (n) SNP/micro
a
(n)
References (n) Populations (n)
Genes (n) Chr. num.
b
Type 1 diabetes mellitus
247
147
15
15
17
4
Multiple sclerosis
64
81
16
15
15
4
Bipolar disorder
58
30
2
2
2
2
Schizophrenia
57
49
8
9
8
8
Age-relatedmacular degeneration 48
61
12
13
13
5
Rheumatoid arthritis
40
58
11
12
12
6
Note: SNP/micro: SNPs and microsatellites; Chr. Num: chromsome number
Haplotypes can contain more information than a
single marker, and can reveal synergistic effects
among SNPs. Thus, haplotypes that are responsible
for some genetic disorders are being developed for
molecular diagnosis of genetic disorders (especially
for autosomal recessive genetic disorders). Some
studies (Basel et al., 2004; Sossenheimer et al., 1997,
Repiso et al., 2005, Lian et al., 2004) have indicated
that haplotype analysis is highly informative for
molecular disease diagnosis and carrier status.
Consequently, by offering detailed information about
complex disease-related haplotypes, CDRH may help
in the design of future experimental and
computational biology studies.
3 Conclusion
CDRH is the first database to emphasize complex
human diseases at the haplotype level by collecting
and cataloguing a great variety of literature. It
provides a user-friendly interface to search for
detailed information concerning haplotypes and
diseases. We encourage researchers to submit
interesting new data and offer a download function.
We are committed to the maintenance and update of
the CDRH database, and hope that it will guide
researchers to a fuller understanding of complex
human diseases.
4 Future Perspective
With the rapid improvement in SNP genotyping
technology and haplotype analysis methods, we can
conveniently obtain genome-wide SNP data. Thus,
genome-wide association studies based on haplotypes
might be an efficient way to identify genetic regions
or genes that are implicated in complex diseases. Our
group will closely follow the future developments in
haplotype studies of complex human diseases, and
provide users with timely information. We believe that
the CDRH database will provide deeper insights into
the relationships between haplotypes and complex
diseases.
Acknowledgments
This work was supported in part by grants from the National
Natural Science Foundation of China (Grant Nos. 81172842,
31200934) and the Natural Science Foundation of Heilongjiang
Province (Grant No. C201206). We thank all members of the
statistical genetics workshop at the College of Bioinformatics
Science and Technology, Harbin Medical University.
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Computational
Molecular Biology