Genome-wide linkage analysis of ADHD using high- density SNP ...

statistical methods into consideration. This approach
compensates for the disadvantage of both the
parametric analyses assuming a disease-model
maximizing the LOD score and the non-parametric
analyses without any model specification, for example,
possibly overestimating versus possibly underestimating
linkage in the respective analyses. Overlapping
results obtained by both parametric (MODglobal and
MODsingle) and non-parametric (NPL) statistical
methods are, therefore, supportive of robust findings.
The linkage scores identified in individual families by
parametric analysis were comparable to NPL scores.
Across all families, however, the total NPL scores were
calculated without considering different degrees of
informativeness between the families, and, therefore,
did not match the respective MOD scores. Although, in
contrast to nearly all previous genome-wide linkage
scans, we discuss only those findings that met the
criteria for genome-wide significance suggested by
Lander and Kruglyak, 34 it ought to be kept in mind that
all findings are nominal and not adjusted for multiple
testing. However, since our intention to obtain comparable
results from various statistical approaches
accounts for the dilemma of multiple testing,
Bonferroni correction would be too conservative.
In conclusion, we detected novel and replicated
several previously reported linkage loci for ADHD.
The considerable overlap with earlier genome-wide
scans indicates that even though the genetic etiology
of ADHD is complex, there is increasing evidence for
common gene effects throughout different populations.
We propose new susceptibility genes with
possible functional relevance in light of existing brain
metabolic models of ADHD. This genome-wide
linkage scan for ADHD employed high marker density
to optimize resolution and novel strategies of data
analysis were applied to meet the statistical demands
imposed by sample structure and marker density. In
contrast to a previously conducted scan in extended
pedigrees, 14 the families are unrelated, ascertained on
the basis of tertiary referral and not part of a genetic
isolate. The investigation of multigenerational pedigrees
is one of the most promising approaches to
identify genetic variants associated with disorders of
multifactorial etiology, as the phenotype within
families is rather homogeneous, and erroneous investigation
of phenocopies is, therefore, highly unlikely.
While several whole genome association
(WGA) studies currently underway will likely clarify
whether common variants explain any of the reported
linkage peaks, some of our findings may represent the
effect of rare alleles that are not detected easily by a
WGA approach. Although specific limitations of the
study design need to be considered, our results
encourage ongoing efforts in the investigation of
multigenerational families with dense segregation of
genetically complex psychiatric disorders. Future
investigations will have to include fine mapping,
positional cloning efforts, WGA studies and metaanalytic
approaches to clarify the relevance of the
present findings.
Genome-wide linkage analysis of ADHD
M Romanos et al
Acknowledgments
We thank all families for their participation and
support. We also greatly appreciate the support from
several co-workers, who contributed to organization
of the study, data management and technical assistance:
Andrea Boreatti-Hümmer, Annette Nowak,
Gabriela Ortega, Ulrike Schülter, Nicole Steigerwald,
Theresia Töpner. We thank Professor Konstantin
Strauch for supporting us in using the program
GENEHUNTER-MODSCORE. This study was supported
by the Deutsche Forschungsgemeinschaft
(DFG: KFO 125, SFB 581, ME 1923/5-1, ME 1923/
5-3, GRK 1389/1) and the Bundesministerium für
Bildung und Forschung (BMBF: 01GV0605).
Conflict of Interest
The authors declare no competing financial interests.
Author contributions: The study was supervised and
directed by KPL, JM, CF and AW. MR, HP, CS and CJ
ascertained and clinically characterized the families.
JR, TR, MH and SW contributed to clinical characterization
of family members. DWC, RB and DAS carried
out the genetic analysis. Fine mapping was carried
out by JS, CV and JM. Data analyses and genotyping
were performed by KPL, MR, TR, AR and co-workers.
Statistical analysis was performed by TN, AD and HS;
CWK contributed to the power analysis. MR, CF, CJ
and KPL wrote and revised the manuscript.
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