André Kleensang

Genome-wide linkage analysis of malaria infection intensity and mild disease.

Although balancing selection with the sickle-cell trait and other red blood cell disorders has emphasized the interaction between malaria and human genetics, no systematic approach has so far been undertaken towards a comprehensive search for human genome variants influencing malaria. By screening 2,551 families in rural Ghana, West Africa, 108 nuclear families were identified who were exposed to hyperendemic malaria transmission and were homozygous wild-type for the established malaria resistance factors of hemoglobin (Hb)S, HbC, alpha+ thalassemia, and glucose-6-phosphate-dehydrogenase deficiency. Of these families, 392 siblings aged 0.5–11 y were characterized for malaria susceptibility by closely monitoring parasite counts, malaria fever episodes, and anemia over 8 mo. An autosome-wide linkage analysis based on 10,000 single-nucleotide polymorphisms was conducted in 68 selected families including 241 siblings forming 330 sib pairs. Several regions were identified which showed evidence for linkage to the parasitological and clinical phenotypes studied, among them a prominent signal on Chromosome 10p15 obtained with malaria fever episodes (asymptotic z score = 4.37, empirical p-value = 4.0 × 10−5, locus-specific heritability of 37.7%; 95% confidence interval, 15.7%–59.7%). The identification of genetic variants underlying the linkage signals may reveal as yet unrecognized pathways influencing human resistance to malaria.

Developmental Dyslexia – Recurrence Risk Estimates from a German Bi-Center Study Using the Single Proband Sib Pair Design

Objective: Several studies have demonstrated a genetic component for dyslexia. However, both segregation and linkage analyses show contradictory results pointing at the necessity of an optimal ascertainment scheme for molecular genetic studies. Previously, we have argued that the single proband sib pair design (SPSP) would be optimal. The aims of this paper therefore are to demonstrate the practicability of the SPSP design and the estimation of recurrence risks for reading and writing. Methods: We assessed spelling and reading in a family sample ascertained through the SPSP design. 287 families with at least two siblings and their parents were recruited. At least one child was affected with spelling disorder according to a one standard deviation (1SD) discrepancy criterion. Results: Mean values for probands and their siblings were different for both the spelling and the reading phenotype. For the probands, variances of the phenotype spelling were smaller. These effects became stronger with more extreme selection criteria. Both siblings fulfilled the 1SD criterion for spelling and reading in 60.3 and 28.9% of the families, respectively, indicating a low cost efficiency of the double proband sib pair approach. A recurrence risk of 4.52 (CI: 4.07–4.93) was obtained for spelling when the 1SD criterion was applied to both siblings. Recurrence risk estimates were similar for reading. Conclusion: The study demonstrates the suitability of the SPSP design for genetic analysis of dyslexia. The recurrence risk estimates may be used for determining sample sizes in gene mapping studies.

Evidence for linkage of restless legs syndrome to chromosome 9p Are there two distinct loci

Background: Restless legs syndrome (RLS) is a common sensory-motor disorder characterized by paresthesias and an intense urge to move the legs with a considerable familial aggregation. To date, no gene mutation has been found, but five gene loci have been mapped in primary RLS to chromosomes 12q, 14q, 9p, 2q, and 20p (RLS1 through 5). Patients/Methods: We identified a four-generational German RLS family with 37 family members including 15 affected cases. We performed linkage analysis using microsatellite markers at the five known loci. Prompted by the identification of a potentially shared haplotype near the RLS3 locus, we expanded the investigated linkage region on chromosome 9p using additional DNA markers. Results: Mode of inheritance in our RLS family was compatible with an autosomal dominant pattern, and disease onset was mainly in childhood or adolescence. We excluded linkage to the RLS1, RLS2, RLS4, and RLS5 loci. However, we identified a likely new RLS gene locus (RLS3*) on chromosome 9p with a maximum lod score of 3.60 generated by model-based multipoint linkage analysis. A haplotype flanked by D9S974 and D9S1118 in a 9.9-Mb region, centromeric to RLS3, was shared by all 12 investigated patients. In addition, 11 of them carried a common haplotype extending telomeric to D9S2189 that is located within RLS3. Conclusions: We demonstrate linkage to a locus on chromosome 9p that is probably distinct from RLS3. Our family with a rather homogeneous phenotype and very early disease onset represents a unique opportunity to further elucidate the genetic causes of the frequent restless leg syndrome.

Interrelationship and Familiality of Dyslexia Related Quantitative Measures

Dyslexia is a complex gene‐environment disorder with poorly understood etiology that affects about 5% of school‐age children. Dyslexia occurs in all languages and is associated with a high level of social and psychological morbidity for the individual and their family; approximately 40‐50% have persistent disability into adulthood. The core symptoms are word reading and spelling deficits, but several other cognitive components influence the core phenotype.

Mapping for dyslexia and related cognitive trait loci provides strong evidence for further risk genes on chromosome 6p21

In a genome‐wide linkage scan, we aimed at mapping risk loci for dyslexia in the German population. Our sample comprised 1,030 individuals from 246 dyslexia families which were recruited through a single‐proband sib pair study design and a detailed assessment of dyslexia and related cognitive traits. We found evidence for a major dyslexia locus on chromosome 6p21. The cognitive trait rapid naming (objects/colors) produced a genome‐wide significant LOD score of 5.87 (P = 1.00 × 10−7) and the implicated 6p‐risk region spans around 10 Mb. Although our finding maps close to DYX2, where the dyslexia candidate genes DCDC2 and KIAA0319 have already been identified, our data point to the presence of an additional risk gene in this region and are highlighting the impact of 6p21 in dyslexia and related cognitive traits.

Linkage analyses of chromosomal region 18p11-q12 in dyslexia

Summary.Dyslexia is characterized as a significant impairment in reading and spelling ability that cannot be explained by low intelligence, low school attendance or deficits in sensory acuity. It is known to be a hereditary disorder that affects about 5% of school aged children, making it the most common of childhood learning disorders. Several susceptibility loci have been reported on chromosomes 1, 2, 3, 6, 15, and 18. The locus on chromosome 18 has been described as having the strongest influence on single word reading, phoneme awareness, and orthographic coding in the largest genome wide linkage study published to date (Fisher et al., 2002). Here we present data from 82 German families in order to investigate linkage of various dyslexia-related traits to the previously described region on chromosome 18p11-q12. Using two- and multipoint analyses, we did not find support for linkage of spelling, single word reading, phoneme awareness, orthographic coding and rapid naming to any of the 14 genotyped STR markers. Possible explanations for our non-replication include differences in study design, limited power of our study and overestimation of the effect of the chromosome 18 locus in the original study.

Human Genetic Resistance to Onchocerca volvulus: Evidence for Linkage to Chromosome 2p from an Autosome-Wide Scan

BACKGROUND Human infections with the tissue nematode Onchocerca volvulus show strong interindividual variation in intensity, which cannot be explained by differences in exposure alone. Several lines of evidence suggest a relevant influence of human genetics. METHODS In a genome-wide search for genetic determinants of resistance, we studied 196 siblings from 51 families exposed to endemic O. volvulus transmission in the forest zone of Ghana, West Africa. The numbers of worm larvae in the skin (i.e., microfilariae), which are the established measure of O. volvulus infection intensity, were counted in 4 small skin biopsy specimens (i.e., skin snips), and the numbers of palpable subcutaneous worm nodules (i.e., onchocercomata) were assessed. Numbers were corrected for age and exposure and were analyzed for linkage to 377 autosomal microsatellite markers and additional markers in genomic regions of interest. RESULTS Linkage was detected between the numbers of microfilariae and chromosome 2p21-p14 (maximum multipoint log(10) of odds (LOD) score of 3.80 at marker position D2S2378; empirical P=2.9 x 10(-5)). CONCLUSIONS This finding provides strong evidence that a human genetic factor influences the intensity of O. volvulus infection. The strength of the linkage signal may facilitate the identification of the decisive genetic variants.

An extensive comparison of quantitative trait loci mapping methods

Background: The choices of study design and statistical approach for mapping a quantitative trait (QT) are of great importance. Larger sibships and a study design based upon phenotypically extreme siblings can be expected to have a greater statistical power. On the other hand, selected samples and/or deviation from normality can influence the robustness and power. Unfortunately, the effects of violation of multivariate normality assumptions and/or selected samples are only known for a limited number of methods. Some recommendations are available in the literature, but an extensive comparison of robustness and power under several different conditions is lacking. Methods: We compared eight freely available and commonly applied QT mapping methods in a Monte-Carlo simulation study under 36 different models and study designs (three genetic models, three selection schemes, two family structures and the possible effect of deviation from normality). Results: Empirical type I error fractions and empirical power are presented and explained as a whole and for each method separately, followed by a thorough discussion. Conclusions: The results from this extensive comparison could serve as a valuable source for the choice of the study design and the statistical approach for mapping a QT.

Haplotype-sharing analysis for alcohol dependence based on quantitative traits and the Mantel statistic

Haplotype-based methods have become increasingly popular in the last decade because shared lengths in haplotypes can be used for disease localization. In this contribution, we propose a novel linkage-based haplotype-sharing approach for quantitative traits based on the class of Mantel statistics which is closely related to the weighted pair-wise correlation statistic. Because these statistics are known to be liberal, we propose a permutation test to evaluate significance. We applied the Mantel statistic to the autosomal data from the genome-wide scan of the Collaborative Study on the Genetics of Alcoholism with the Affymetrix Genotype 10 K array that was provided for the Genetic Analysis Workshop 14. Four regions on chromosome 4, 8, 16, and 20 showed p-values less than 0.005 with a minimum p-value of < 0.0001 on chromosome 16 (tsc0520638 at 72.8 cM). Three of these four regions located on chromosome 4, 16, and 20 have been reported previously in the Genetic Analysis Workshop 11.

More powerful haplotype sharing by accounting for the mode of inheritance

The concept of haplotype sharing (HS) has received considerable attention recently, and several haplotype association methods have been proposed. Here, we extend the work of Beckmann and colleagues [2005 Hum. Hered. 59:67–78] who derived an HS statistic (BHS) as special case of Mantels space‐time clustering approach. The Mantel‐type HS statistic correlates genetic similarity with phenotypic similarity across pairs of individuals. While phenotypic similarity is measured as the mean‐corrected cross product of phenotypes, we propose to incorporate information of the underlying genetic model in the measurement of the genetic similarity. Specifically, for the recessive and dominant modes of inheritance we suggest the use of the minimum and maximum of shared length of haplotypes around a marker locus for pairs of individuals. If the underlying genetic model is unknown, we propose a model‐free HS Mantel statistic using the max‐test approach. We compare our novel HS statistics to BHS using simulated case‐control data and illustrate its use by re‐analyzing data from a candidate region of chromosome 18q from the Rheumatoid Arthritis (RA) Consortium. We demonstrate that our approach is point‐wise valid and superior to BHS. In the re‐analysis of the RA data, we identified three regions with point‐wise P‐values<0.005 containing six known genes (PMIP1, MC4R, PIGN, KIAA1468, TNFRSF11A and ZCCHC2) which might be worth follow‐up. Genet. Epidemiol. 2009.