A genome-wide screen for acrophobia susceptibility loci in a finnish isolate

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A genome-wide screen for acrophobia susceptibility loci in a finnish isolate"


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ABSTRACT Acrophobia, an abnormal fear of heights, is a specific phobia characterized as apprehension cued by the occurrence or anticipation of elevated spaces. It is considered a complex


trait with onset influenced by both genetic and environmental factors. Identification of genetic risk variants would provide novel insight into the genetic basis of the fear of heights


phenotype and contribute to the molecular-level understanding of its aetiology. Genetic isolates may facilitate identification of susceptibility alleles due to reduced genetic heterogeneity.


We took advantage of an internal genetic isolate in Finland in which a distinct acrophobia phenotype appears to be segregating in pedigrees originally ascertained for schizophrenia. We


conducted parametric, nonparametric, joint linkage and linkage disequilibrium analyses using a microsatellite marker panel, genotyped in families to search for chromosomal regions correlated


with acrophobia. Our results implicated a few regions with suggestive evidence for linkage on chromosomes 4q28 (LOD = 2.17), 8q24 (LOD = 2.09) and 13q21-q22 (LOD = 2.22). We observed no


risk haplotypes shared between different families. These results suggest that genetic predisposition to acrophobia in this genetic isolate is unlikely to be mediated by a small number of


shared high-risk alleles, but rather has a complex genetic architecture. SIMILAR CONTENT BEING VIEWED BY OTHERS COMPLEX TRAIT SUSCEPTIBILITIES AND POPULATION DIVERSITY IN A SAMPLE OF 4,145


RUSSIANS Article Open access 23 July 2024 POLYGENIC CONTRIBUTION TO THE RELATIONSHIP OF LONELINESS AND SOCIAL ISOLATION WITH SCHIZOPHRENIA Article Open access 10 January 2022 INSIGHTS FROM


THE LARGEST DIVERSE ANCESTRY SEX-SPECIFIC DISEASE MAP FOR GENETICALLY PREDICTED HEIGHT Article Open access 27 February 2025 INTRODUCTION Acrophobia is a pervasive mental disorder, also known


as an irrational fear of heights, affecting approximately five percent of the world’s population1. It is a disproportional reaction to a common, rational fear, and can be characterized as


apprehension, triggered by elevated spaces or anticipation of them. Acrophobia is classified as a specific phobia under the Diagnostic and Statistical Manual of Mental Disorders (DSM-V), and


its aetiology is influenced by both genetic and environmental factors2,3. While demonstrating high comorbidity rates with various psychiatric disorders and diseases, such as different


anxiety disorders or major depression4,5, acquisition of acrophobia is believed to differ from other phobias. It may be mediated through a non-associative pathway6, rather than conditioning


or learning from negative or traumatic experiences7. The symptoms of individuals suffering from acrophobia involve changes in behavioural, cognitive and physiological functioning, such as


confusion and dizziness, when exposed to heights7. Physiologically associated with anomalies in balance control and avoidance behaviour, acrophobia is a consequence of an underlying


biological anomaly involving impaired visual detection of body sway8. In healthy subjects, posture control is obtained by integrated processing of vestibular, visual and proprioceptive


inputs9. However, in people suffering from acrophobia, dysfunction in one of the feedback mechanisms may lead to increased dependence on other stimuli. In particular, the presence of


vestibular dysfunction causes increased dependence on visual or proprioceptive information to keep balance and constant anticipation of matching the natural oscillation of body sway with


visual flow stimulation7. This matching is the root cause of the feeling of lack of stability, especially when exposed to high places10. Although the biological mechanisms of acrophobia have


been thoroughly investigated8, little is known about its molecular basis. As in the case of other complex psychiatric diseases, efforts to localize genetic variants predisposing to


acrophobia are hindered by the complexity of the clinical phenotype and the heterogeneity of the studied samples11. Therefore, isolated populations offer several advantages in studying the


genetic architecture of such complex human diseases, both when rare12,13 or common14 variants are thought to be involved in the genetic aetiology of the condition. Firstly, the enrichment of


the risk alleles in an isolated population might help enable their identification. Furthermore, the shared environmental and cultural homogeneity is highly beneficial as potent exposures to


environmental risks during the lifetime, possibly influencing the aetiology of the disorder, are not routinely evaluated and might therefore be difficult to detect11. To reduce genetic


heterogeneity we have used an isolated homogenous population from north-eastern Finland with small number of founders. This population, described elsewhere15,16, has been intensively


characterized using multiple high-quality historical and health-care registries and was previously studied due to increased lifetime risk of schizophrenia, compared with the rest of


Finland17. While the collection of the schizophrenia sample was ongoing, we observed that a large number of family members had distinct and severe acrophobia that segregated independently


from schizophrenia. In this study, we aimed to map genetic loci predisposing to this specific phenotype. We hypothesized that predisposition to acrophobia may be mediated by a small number


of high risk susceptibility variants segregating in this isolate, and that we could possibly identify them through a genome-wide linkage scan using microsatellite markers, which had been


genotyped as a part of earlier linkage-based gene mapping studies17,18. RESULTS Our sample was composed mostly of large multigenerational pedigrees with multiple individuals affected with


acrophobia and at least one parent born in the isolate (Fig. 1). It included 642 people, 42 of them affected only with acrophobia (6.5%) and 75 with acrophobia comorbid with schizophrenia


(11.7%; Table 1). As part of earlier studies17,18, we had genotype information available from 367 individuals, assessed by a genome-wide microsatellite marker panel. As parametric and


nonparametric (model-free) methods have different strengths and weaknesses in detecting linkage19, we applied both techniques across the genome. Two-point parametric analysis has been proven


to be more powerful than nonparametric analysis, provided that the trait and marker locus are specified correctly. However, in case the parametric model is incorrect, the power of the


parametric linkage might be exceeded by nonparametric methods. As the inheritance pattern in our study is unknown, we decided to conduct analyses with both methods. In the parametric


analysis, we used dominant and recessive models due to unknown inheritance pattern, followed by nonparametric analysis, and joint linkage and linkage disequilibrium analysis (Fig. 2). While


two-point analysis examines linkage of a disease to a single marker locus at a time, multipoint analysis evaluates linkage to multiple markers simultaneously. This results in a greater power


to detect linkage, but also an inflation of type I error (false positive) if marker-related information is incorrect20. We performed multipoint, but not two-point nonparametric analysis,


because of the limitations in the size of the pedigrees, which can be analysed, without being divided, by currently available software21. Due to the significant number of individuals with


acrophobia comorbid with schizophrenia, we analysed all individuals with acrophobia, but also conducted separate analyses with individuals with pure acrophobia and pure schizophrenia to


investigate whether any signal was mainly coming from genetic factors influencing susceptibility to schizophrenia independent of acrophobia. PARAMETRIC TWO-POINT RECESSIVE AND DOMINANT


LINKAGE ANALYSIS We first carried out parametric two-point linkage analysis to identify genetic regions linked with acrophobia. The strongest evidence for linkage in the acrophobia sample


(including cases with comorbid schizophrenia) was obtained with marker D5S2115 (LOD = 2.16) using a dominant model. In the pure acrophobia sample, the same marker yielded a LOD score of 0.58


(dominant model), suggesting that this finding may be mainly driven by the schizophrenia phenotype. This was further confirmed by analysing all individuals with schizophrenia without


comorbid acrophobia (LOD = 1.57, dominant model). For the pure acrophobia sample, we obtained the highest LOD score with marker D8S373 (LOD = 2.09) adopting a recessive inheritance model.


Since in the acrophobia with comorbid schizophrenia sample the same marker yielded a LOD score of 0.51 (recessive model) and in the pure schizophrenia sample a LOD score of 0.00 (recessive


model), this signal may be produced mainly by the acrophobia phenotype. Table 2 shows the results of the two-point analyses for markers giving the strongest evidence of linkage (LOD score of


>1.6). PARAMETRIC MULTIPOINT LINKAGE ANALYSIS We carried out parametric multipoint analysis for chromosomes with markers and models which yielded LOD score of >2.0 in at least one


parametric two-point analysis (chromosome 5: dominant model in acrophobia with comorbid schizophrenia; and chromosome 8: recessive model in pure acrophobia). In the acrophobia sample


(including cases with comorbid schizophrenia), marker D5S2115 yielded a maximum LOD score of 0.054 (α = 0.15, dominant model). In the pure acrophobia sample the highest LOD score on


chromosome 8 was with marker D8S373 (0.533, α = 1.00, recessive model). NONPARAMETRIC MULTIPOINT LINKAGE ANALYSIS We next carried out multipoint nonparametric genome-wide linkage analysis


with empirical NPL_ALL model (Fig. 3), measuring if a few founder-alleles are overly represented in affected individuals. Among the acrophobia sample (including cases with comorbid


schizophrenia), the maximum LOD score of 2.91 was detected with marker D13S173, while for the pure acrophobia sample the same marker reached LOD score of 2.11. In the pure acrophobia sample


the most significant evidence of linkage (LOD score = 2.22) was observed with marker D13S162. Markers D13S173 and D13S162 are located 37.8 cM apart and are therefore not strongly linked.


Figure 4 shows the results from the multipoint nonparametric linkage analysis with empirical NPL_PAIR model measuring the sum of conditional kinship coefficients for all affected pairs. For


acrophobia sample (including cases with comorbid schizophrenia), NPL_PAIR approach yielded the maximum LOD score with marker D1S2817 (LOD = 2.52), while in the pure acrophobia sample the LOD


score for the same marker was 0.47. The strongest finding for NPL_PAIR analysis in the pure acrophobia sample was a LOD score of 2.17 with marker D4S2394. JOINT LINKAGE AND LINKAGE


DISEQUILIBRIUM ANALYSIS We hypothesized that reduced genetic heterogeneity in the genetic isolate would lead to the majority of the cases carrying the same predisposing variant, detectable


as linkage disequilibrium (LD). Therefore, we performed PSEUDOMARKER analysis of LD conditional on linkage (Fig. 5). The strongest evidence for association to acrophobia (including cases


with comorbid schizophrenia) was detected for markers D4S2431 (P = 0.0003, recessive model) and D14S267 (P = 0.0019, dominant model). In the pure acrophobia sample the same markers yielded P


values of 0.1704 and 0.0244, respectively. For the pure acrophobia sample the strongest association was obtained to markers D17S2196 (P = 0.0054, dominant model) and D1S235 (P = 0.0054,


recessive model). These results are consistent with the lack of evidence of linkage in the sample. POWER SIMULATION To test the statistical power of the analysed sample, we performed


simulation with SLINK22 software. We obtained average maximum LOD scores of 5.77 and 5.03 with the dominant and recessive model, respectively. Furthermore, 31% of replicates under the


dominant and 12% of replicates under the recessive model reached the conventional LOD score threshold of 3.0. Therefore, this sample has adequate statistical power to obtain significant


evidence for linkage to major loci predisposing to acrophobia. DISCUSSION We aimed to find genetic loci predisposing to acrophobia in a genetically isolated population with the hypothesis


that due to reduced genetic heterogeneity, a few risk alleles predisposing to the phenotype might be identified. While several loci attained LOD score of >2.0, we observed no genome-wide


significant evidence for linkage at any of the studied markers. We detected the strongest evidence of linkage to acrophobia on chromosomal region 13q21-q22 with a peak on marker D13S162 (LOD


 = 2.22; pure acrophobia sample). To our knowledge, this region has not been previously associated with phobias or other anxiety disorders. SNP rs2323266, located 14.01 Mb from marker


D13S162 and close to the protocadherin 20 (_PCDH20_) gene in this region, has been previously connected to positive symptom dimension in a genome-wide association study (GWAS) of


schizophrenia (P = 3 × 10−6)23. However, markers D13S162 and rs2323266 are not located within the same LD block. Thus, in our sample, the finding in this chromosomal region seemed to be


specific for acrophobia. We obtained the second strongest evidence of linkage for acrophobia on chromosomal region 4q28 for marker D4S2394 (LOD = 2.17; pure acrophobia sample). Again, in our


study, this signal appeared to be mainly coming from acrophobia and not schizophrenia phenotype (LOD = 0.52; pure schizophrenia sample). This region has not been previously associated with


anxiety disorders or schizophrenia. Chromosomal region 8q24.2-q24.3 with marker D8S373 (LOD = 2.09) was the third region most strongly linked to acrophobia. It has previously been associated


with bipolar disorder24,25,26 and schizophrenia27. However, in our samples of acrophobia with comorbid schizophrenia (LOD = 0.51) and pure schizophrenia (LOD = 0.00) this region did not


provide evidence for linkage. This region encompasses 49 genes, including several candidate genes for psychiatric disorders: potassium voltage-gated channel subfamily KQT member 3


(_KCNQ3_)24,28 coding for a voltage-gated potassium channel; adenylate cyclase 8 (_ADCY8_)24 involved in fear learning and memory, and long-term memory consolidation29; Ly6/Neurotoxin 1


(_LYNX1_)30 (located on 8q24.3 near D8S373) involved in the development of visual perception including binocular vision and motor learning during the critical period31,32,33,34; and


activity-regulated cytoskeleton-associated protein (_ARC_)29 connected to long-term potentiation and the consolidation of long-term memory. Our strongest evidence for LD conditional on


linkage (P = 0.0054, dominant model) was observed with markers located in chromosomal region 17p11. The region harbours hundreds of genes, however, to our knowledge, none of them have been


previously directly connected to phobias or other anxiety disorders. Several of the chromosomal regions we identified seemed mainly specific for schizophrenia. The most significant of those


regions were 5q31 and 1q32, discussed above for markers D5S2115 and D1S2817. Both of them have been previously associated with schizophrenia in numerous studies35,36,37,38. Furthermore,


several markers on the long arm of chromosome 13, localized between 13q31 and 13q33, showed evidence of linkage (LOD > 2.0) to both pure acrophobia and acrophobia with comorbid


schizophrenia, and also weak linkage to pure schizophrenia (maximum LOD = 1.26). Therefore, this region may harbour variants influencing susceptibility to both phenotypes. As specific phobia


subtypes have high comorbidity with other anxiety disorders4 and psychiatric disorders, such as schizophrenia39, the same genetic variants affecting brain function may be involved in both


diseases partially explaining the high comorbidity rates and overlapping biological symptoms. Intriguingly, several shared symptoms related to balance control and avoidance behaviour,


central in acrophobia, have been described in schizophrenia and depressive disorders. Most importantly, irregularities in eye movement and head coordination propensities associated with


difficulties in classification of relevant visual stimuli have been observed in schizophrenia patients40. Furthermore, the primary vestibular disfunction leading to chronic dizziness occurs


both in specific phobias and depressive disorders41. Lastly, acrophobia is a significant predictor of later depressive episodes, generalized anxiety and panic attacks42. Together, these


observations may be related to partially shared genetic predisposition to acrophobia and other comorbid psychiatric diseases, including schizophrenia. We recognise the hypothesis-generating


character of our study. It included a large number of genotyped markers (570) and analysed models (6). Although this serves to strengthen the study, it inevitably lead to multiple


statistical testing. However, as the tests carried out are not completely independent, the adjustment for multiple testing is not straightforward43. Consequently, avoidance of the type I


error might unintentionally inflate the type II error (false negative). Therefore, we decided to provide the LOD scores and their corresponding uncorrected nominal P values, when applicable,


and rely on the future studies of acrophobia in independent samples to assess whether the chromosomal regions identified in this study harbor true predisposing variants. In recent years,


single nucleotide polymorphisms (SNPs) have replaced microsatellite markers due to their lower genotyping costs. This technical advance has enabled genome-wide association studies (GWASs) in


which thousands of individuals are genotyped. Consequently, the usage of microsatellite markers, a class of short tandem repeats (STRs), has severely decreased. However, due to their highly


polymorphic nature microsatellites are still considered more informative than the diallelic SNPs44 in studying the genetic architecture of complex human diseases. Unlike in the


population-based association studies, the enrichment of the risk alleles in isolated populations and higher degree of LD may enable the identification of genetic risk factors in a smaller


sample and with smaller number of markers, as shown previously for neuropsychiatric diseases, such as schizophrenia and autism11,17,45. In conclusion, our findings suggest that the genetic


basis of acrophobia is highly complex, even in this genetic isolate, as we were not able to identify high-risk variants shared by several families. However, we identified several chromosomal


regions with suggestive evidence for linkage which could be investigated further in other acrophobia samples and meta-analyses of such datasets having an increased statistical power.


METHODS STUDY SAMPLE The sample was composed mostly of large multigenerational pedigrees with multiple affected individuals and at least one parent born in the isolate (Fig. 1). It comprised


57 families including 642 people, 75 of them affected with acrophobia and schizophrenia (11.7%) and 42 with pure acrophobia (6.5%). All pedigrees are part of a Finnish severe mental


disorders family collection of the National Institute for Health and Welfare17,18,46,47. We traced ancestors from Finnish Population Registries and performed a genealogical study in


accordance with published criteria47. Data from psychiatric case notes and treatment facilities concerning affected individuals and blood samples were collected between 1991 and 200248.


Structured Clinical Interviews for DSM-IV (SCID-I)49 followed by a diagnostic assessment performed in accordance with the Diagnostic and Statistical Manual of Mental Disorders, 4th edition


(DSM-IV) criteria50 and Operational Criteria Checklist (OPCRIT)44 were conducted at a later time, between 1998 and 200248. Following the interviews, assessment was undertaken independently


by two psychiatrists (T.Par. and R.A.). In case of disagreement, third psychiatrist (J.L.), reanalysed the case in order to gain consensus17. The sample used in the study is detailed in


Table 1. The ethical review board of the National Institute for Health and Welfare (THL), formerly the National Public Health Institute of Finland (KTL), approved all experimental protocols


in this study and the methods used were carried out in accordance with the approved guidelines. Informed consent was obtained from all participants before enrolment in the study. GENOTYPING


We analysed 575 autosomal microsatellite markers across the genome that had been genotyped as a part of earlier linkage-based gene mapping studies17,48. We had genotype information available


from all affected and 292 unaffected individuals. STATISTICAL ANALYSES We performed statistical analyses separately for acrophobia with comorbid schizophrenia and pure acrophobia sample to


discriminate between the possible shared and separate genetic signals associated with the phenotypes. We further followed with statistical analysis of the pure schizophrenia sample for the


most interesting results. We first checked all genotypes for Mendelian inconsistencies with PedCheck software51 and removed erroneous genotypes, which accounted for less than 0.08% of all


genotypes. We performed all analyses as affected-only, meaning that all phenotypes of healthy individuals and those with unknown affection status were treated as _unknown_, due to the fact


that unaffected family members were not systematically assessed52. PARAMETRIC TWO-POINT RECESSIVE AND DOMINANT LINKAGE ANALYSIS We performed two-point parametric linkage analysis with


statistical software package FASTLINK 4.1 P under a recessive and dominant mode of inheritance with, respectively, penetrance of 0.001% and 90%, disease allele frequency of 0.00001 and 0.01,


and phenocopy rates of 0 and 0.01. FASTLINK 4.1 P program was implemented in a helper program AUTOGSCAN53. PARAMETRIC AND NONPARAMETRIC MULTIPOINT LINKAGE ANALYSIS We carried out multipoint


parametric and nonparametric linkage analysis with SimWalk2 version 2.9654,55,56. For the nonparametric analysis, two statistics were examined: empirical NPL_ALL model, measuring if few


founder-alleles are overly represented in affected individuals, and NPL_PAIR, measuring the sum of conditional kinship coefficients for all affected pairs. In all analyses, pedigrees with


just one, non-related affected, were not analysed by the program, limiting the total number of pedigrees evaluated to five for pure acrophobia and 15 for acrophobia with comorbid


schizophrenia sample. Files for SimWalk2 software were prepared with free data conversion program Mega257. STAGE III: JOINT LINKAGE AND LINKAGE DISEQUILIBRIUM (LD) ANALYSIS We performed the


linkage disequilibrium conditional on linkage analysis with PSEUDOMARKER software package under default dominant and recessive models58,59. PSEUDOMARKER program uses a likelihood-based


method, which combines pedigrees of heterogeneous relationship structures, singletons and others, into one unified analysis. POWER SIMULATION The power of the analysed pedigrees to detect


linkage was estimated with SLINK simulation program and the replicates were analysed with ISIM analysis program implemented in SLINK package23. The analysis was performed under PSEUDOMARKER


recessive and dominant models with the assumption of complete linkage (θ = 0.0) between marker and trait locus, and with penetrance and disease allele frequency identical to those used in


the linkage analysis. We assumed the disease prevalence of five percent1 for acrophobia. The analysis was performed using 100 replications. ADDITIONAL INFORMATION HOW TO CITE THIS ARTICLE:


Misiewicz, Z. _et al_. A genome-wide screen for acrophobia susceptibility loci in a Finnish isolate. _Sci. Rep._ 6, 39345; doi: 10.1038/srep39345 (2016). PUBLISHER'S NOTE: Springer


Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. REFERENCES * Coelho, C. M. & Wallis, G. Deconstructing acrophobia:


physiological and psychological precursors to developing a fear of heights. Depress. Anxiety 27, 864–870 (2010). Article  PubMed  Google Scholar  * Loken, E. K., Hettema, J. M., Aggen, S. H.


& Kendler, K. S. The structure of genetic and environmental risk factors for fears and phobias. Psychol. Med. 44, 2375–2384 (2014). Article  CAS  PubMed  PubMed Central  Google Scholar


  * Van Houtem, C. M. et al. A review and meta-analysis of the heritability of specific phobia subtypes and corresponding fears. J. Anxiety Disord. 27, 379–388 (2013). Article  CAS  PubMed 


Google Scholar  * Curtis, G. C., Magee, W. J., Eaton, W. W., Wittchen, H. U. & Kessler, R. C. Specific fears and phobias. Epidemiology and classification. Br. J. Psychiatry 173, 212–217


(1998). Article  CAS  PubMed  Google Scholar  * Choy, Y., Fyer, A. J. & Lipsitz, J. D. Treatment of specific phobia in adults. Clin. Psychol. Rev. 27, 266–286 (2007). Article  PubMed 


Google Scholar  * Boffino, C. C. et al. Fear of heights: cognitive performance and postural control. Eur. Arch. Psychiatry Clin. Neurosci. 259, 114–119 (2009). Article  PubMed  Google


Scholar  * Hüweler, R., Kandil, F. I., Alpers, G. W. & Gerlach, A. L. The impact of visual flow stimulation on anxiety, dizziness, and body sway in individuals with and without fear of


heights. Behav. Res. Ther. 47, 345–352 (2009). Article  PubMed  Google Scholar  * Brandt, T., Kugler, G., Schniepp, R., Wuehr, M. & Huppert, D. Acrophobia impairs visual exploration and


balance during standing and walking. Ann. N. Y. Acad. Sci. 1343, 37–48 (2015). Article  ADS  PubMed  Google Scholar  * Maurer, C., Mergner, T. & Peterka, R. J. Multisensory control of


human upright stance. Exp. Brain Res. 171, 231–250 (2006). Article  CAS  PubMed  Google Scholar  * Nakahara, H., Takemori, S. & Tsuruoka, H. Influence of height on the spatial


orientation and equilibrium of the body. Otolaryngol. Head. Neck. Surg. 123, 501–504 (2000). Article  CAS  PubMed  Google Scholar  * Peltonen, L., Palotie, A. & Lange, K. Use of


population isolates for mapping complex traits. Nat. Rev. Genet. 1, 182–190 (2000). Article  CAS  PubMed  Google Scholar  * Sullivan, P. F., Daly, M. J. & O’Donovan, M. Genetic


architectures of psychiatric disorders: the emerging picture and its implications. Nat. Rev. Genet. 13, 537–551 (2012). Article  CAS  PubMed  PubMed Central  Google Scholar  * Ott, J., Wang,


J. & Leal, S. M. Genetic linkage analysis in the age of whole-genome sequencing. Nat. Rev. Genet. 16, 275–284 (2015). Article  CAS  PubMed  PubMed Central  Google Scholar  * Stoll, G.


et al. Deletion of TOP3beta, a component of FMRP-containing mRNPs, contributes to neurodevelopmental disorders. Nat. Neurosci. 16, 1228–1237 (2013). Article  CAS  PubMed  PubMed Central 


Google Scholar  * Hovatta, I. et al. Schizophrenia in the genetic isolate of Finland. Am. J. Med. Genet. 74, 353–360 (1997). Article  CAS  PubMed  Google Scholar  * Varilo, T. et al. Linkage


disequilibrium in isolated populations: Finland and a young sub-population of Kuusamo. Eur. J. Hum. Genet. 8, 604–612 (2000). Article  CAS  PubMed  Google Scholar  * Hovatta, I. et al. A


genomewide screen for schizophrenia genes in an isolated Finnish subpopulation, suggesting multiple susceptibility loci. Am. J. Hum. Genet. 65, 1114–1124 (1999). Article  CAS  PubMed  PubMed


Central  Google Scholar  * Wedenoja, J. et al. Replication of linkage on chromosome 7q22 and association of the regional Reelin gene with working memory in schizophrenia families. Mol.


Psychiatry 13, 673–684 (2008). Article  CAS  PubMed  Google Scholar  * Ott, J. Methods of analysis and resources available for genetic trait mapping. J. Hered. 90, 68–70 (1999). Article  CAS


  PubMed  Google Scholar  * Kruglyak, L., Daly, M. J., Reeve-Daly, M. P. & Lander, E. S. Parametric and nonparametric linkage analysis: a unified multipoint approach. Am. J. Hum. Genet.


58, 1347–1363 (1996). PubMed  PubMed Central  CAS  Google Scholar  * Dudbridge, F. A survey of current software for linkage analysis. Hum. Genomics 1, 63–65 (2003). Article  CAS  PubMed 


PubMed Central  Google Scholar  * Weeks, D. E., Ott, J. & Lathrop, G. M. SLINK: a general simulation program for linkage analysis. Am. J. Hum. Genet. 47, A204 (1990). Google Scholar  *


Fanous, A. H. et al. Genome-wide association study of clinical dimensions of schizophrenia: polygenic effect on disorganized symptoms. Am. J. Psychiatry 169, 1309–1317 (2012). Article 


PubMed  PubMed Central  Google Scholar  * Avramopoulos, D. et al. Linkage of bipolar affective disorder on chromosome 8q24: follow-up and parametric analysis. Mol. Psychiatry 9, 191–196


(2004). Article  CAS  PubMed  Google Scholar  * Gonzalez, S. et al. A genome-wide linkage scan of bipolar disorder in Latino families identifies susceptibility loci at 8q24 and 14q32. Am. J.


Med. Genet. B. Neuropsychiatr. Genet. 165B, 479–491 (2014). Article  PubMed  CAS  Google Scholar  * Kaminsky, Z. et al. DNA methylation and expression of KCNQ3 in bipolar disorder. Bipolar


Disord. 17, 150–159 (2015). Article  CAS  PubMed  Google Scholar  * Holmans, P. A. et al. Genomewide linkage scan of schizophrenia in a large multicenter pedigree sample using single


nucleotide polymorphisms. Mol. Psychiatry 14, 786–795 (2009). Article  CAS  PubMed  PubMed Central  Google Scholar  * Wang, H. S. et al. KCNQ2 and KCNQ3 potassium channel subunits: molecular


correlates of the M-channel. Science 282, 1890–1893 (1998). Article  ADS  CAS  PubMed  Google Scholar  * Wolf, E. J. et al. A genome-wide association study of clinical symptoms of


dissociation in a trauma-exposed sample. Depress. Anxiety 31, 352–360 (2014). Article  CAS  PubMed  PubMed Central  Google Scholar  * Hu, J. et al. A novel maternally inherited 8q24.3 and a


rare paternally inherited 14q23.3 CNVs in a family with neurodevelopmental disorders. Am. J. Med. Genet. A. 167, 1921–1926 (2015). Article  CAS  Google Scholar  * Miwa, J. M. & Walz, A.


Enhancement in motor learning through genetic manipulation of the Lynx1 gene. PLoS One 7, e43302 (2012). Article  ADS  CAS  PubMed  PubMed Central  Google Scholar  * Morishita, H., Miwa, J.


M., Heintz, N. & Hensch, T. K. Lynx1, a cholinergic brake, limits plasticity in adult visual cortex. Science 330, 1238–1240 (2010). Article  ADS  CAS  PubMed  PubMed Central  Google


Scholar  * Hensch, T. K. Critical period regulation. Annu. Rev. Neurosci. 27, 549–579 (2004). Article  CAS  PubMed  Google Scholar  * Parker, A. J. Binocular depth perception and the


cerebral cortex. Nat. Rev. Neurosci. 8, 379–391 (2007). Article  CAS  PubMed  Google Scholar  * Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from


108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014). * McClay, J. L. et al. Genome-wide pharmacogenomic study of neurocognition as an indicator of antipsychotic treatment


response in schizophrenia. Neuropsychopharmacol. 36, 616–626 (2011). Article  CAS  Google Scholar  * Betcheva, E. T. et al. Whole-genome-wide association study in the Bulgarian population


reveals HHAT as schizophrenia susceptibility gene. Psychiatr. Genet. 23, 11–19 (2013). Article  CAS  PubMed  Google Scholar  * International Schizophrenia Consortium et al. Common polygenic


variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009). Article  PubMed Central  CAS  Google Scholar  * Huppert, J. D. & Smith, T. E. Anxiety and


schizophrenia: the interaction of subtypes of anxiety and psychotic symptoms. CNS Spectr. 10, 721–731 (2005). Article  PubMed  Google Scholar  * Proudlock, F. A. & Gottlob, I.


Physiology and pathology of eye-head coordination. Prog. Retin. Eye Res. 26, 486–515 (2007). Article  PubMed  Google Scholar  * Peluso, E. T., Quintana, M. I. & Gananca, F. F. Anxiety


and depressive disorders in elderly with chronic dizziness of vestibular origin. Braz J. Otorhinolaryngol. 82, 209–214 (2016). Article  PubMed  Google Scholar  * Kapfhammer, H. P., Huppert,


D., Grill, E., Fitz, W. & Brandt, T. Visual height intolerance and acrophobia: clinical characteristics and comorbidity patterns. Eur. Arch. Psychiatry Clin. Neurosci. 265, 375–385


(2015). Article  PubMed  Google Scholar  * Freimer, N. & Sabatti, C. The use of pedigree, sib-pair and association studies of common diseases for genetic mapping and epidemiology. Nat.


Genet. 36, 1045–1051 (2004). Article  CAS  PubMed  Google Scholar  * Schaid, D. J. et al. Comparison of Microsatellites Versus Single-Nucleotide Polymorphisms in a Genome Linkage Screen for


Prostate Cancer Susceptibility Loci. Am. J. Hum. Genet. 75, 948–965 (2004). Article  CAS  PubMed  PubMed Central  Google Scholar  * Lauritsen, M. B. et al. A genome-wide search for alleles


and haplotypes associated with autism and related pervasive developmental disorders on the Faroe Islands. Mol. Psychiatry 11, 37–46 (2006). Article  CAS  PubMed  Google Scholar  * Paunio, T.


et al. Linkage analysis of schizophrenia controlling for population substructure. Am. J. Med. Genet. B. Neuropsychiatr. Genet. 150B, 827–835 (2009). Article  PubMed  PubMed Central  Google


Scholar  * Varilo, T. et al. The age of human mutation: genealogical and linkage disequilibrium analysis of the CLN5 mutation in the Finnish population. Am. J. Hum. Genet. 58, 506–512


(1996). PubMed  PubMed Central  CAS  Google Scholar  * Arajärvi, R. et al. Psychosis among “healthy” siblings of schizophrenia patients. BMC Psychiatry 6, 6 (2006). Article  PubMed  PubMed


Central  Google Scholar  * First, M. B., Spitzer, R. L., Gibbon, M. & Williams, J. B. W. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition


(SCID-I/P) (Biometrics Research, New York State Psychiatric Institute, 2002). * McGuffin, P., Farmer, A. & Harvey, I. A polydiagnostic application of operational criteria in studies of


psychotic illness. Development and reliability of the OPCRIT system. Arch. Gen. Psychiatry 48, 764–770 (1991). Article  CAS  PubMed  Google Scholar  * O’Connell, J. R. & Weeks, D. E.


PedCheck: a program for identification of genotype incompatibilities in linkage analysis. Am. J. Hum. Genet. 63, 259–266 (1998). Article  PubMed  PubMed Central  Google Scholar  * Wedenoja,


J. et al. Replication of association between working memory and Reelin, a potential modifier gene in schizophrenia. Biol. Psychiatry 67, 983–991 (2010). Article  CAS  PubMed  Google Scholar


  * Hiekkalinna, T., Terwilliger, J. D., Sammalisto, S., Peltonen, L. & Perola, M. AUTOGSCAN: powerful tools for automated genome-wide linkage and linkage disequilibrium analysis. Twin


Res. Hum. Genet. 8, 16–21 (2005). Article  PubMed  Google Scholar  * Sobel, E. & Lange, K. Descent graphs in pedigree analysis: applications to haplotyping, location scores, and


marker-sharing statistics. Am. J. Hum. Genet. 58, 1323–1337 (1996). PubMed  PubMed Central  CAS  Google Scholar  * Sobel, E., Sengul, H. & Weeks, D. E. Multipoint estimation of


identity-by-descent probabilities at arbitrary positions among marker loci on general pedigrees. Hum. Hered. 52, 121–131 (2001). Article  CAS  PubMed  Google Scholar  * Lange, E. M. &


Lange, K. Powerful allele sharing statistics for nonparametric linkage analysis. Hum. Hered. 57, 49–58 (2004). Article  PubMed  Google Scholar  * Mukhopadhyay, N., Almasy, L., Schroeder, M.,


Mulvihill, W. P. & Weeks, D. E. Mega2: data-handling for facilitating genetic linkage and association analyses. Bioinformatics 21, 2556–2557 (2005). Article  CAS  PubMed  Google Scholar


  * Hiekkalinna, T. et al. PSEUDOMARKER: a powerful program for joint linkage and/or linkage disequilibrium analysis on mixtures of singletons and related individuals. Hum. Hered. 71,


256–266 (2011). Article  PubMed  PubMed Central  Google Scholar  * Gertz, E. M. et al. PSEUDOMARKER 2.0: efficient computation of likelihoods using NOMAD. BMC Bioinformatics 15, 47 (2014).


Article  PubMed  PubMed Central  CAS  Google Scholar  * Wigginton, J. E. & Abecasis, G. R. PEDSTATS: descriptive statistics, graphics and quality assessment for gene mapping data.


Bioinformatics 21, 3445–3447 (2005). Article  CAS  PubMed  Google Scholar  Download references ACKNOWLEDGEMENTS We thank Dr. Ritva Arajärvi, M.D., Ph.D., for help with data collection, Marc


Llort Asens for assistance with formatting the figures, and Lea Urpa for proofreading the manuscript. This work has been supported by Doctoral Program Brain & Mind, University of


Helsinki (Z.M.), Academy of Finland (I.H., J.T.), and Sigrid Jusélius Foundation (I.H.). AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of Biosciences, University of Helsinki,


Helsinki, Finland Zuzanna Misiewicz & Iiris Hovatta * Department of Health, National Institute for Health and Welfare, Helsinki, Finland Tero Hiekkalinna, Tiina Paunio, Joseph D.


Terwilliger, Timo Partonen & Iiris Hovatta * Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland Tero Hiekkalinna * Department of Psychiatry, University


of Helsinki and Helsinki University Hospital, Helsinki, Finland Tiina Paunio * Development of Work and Work Organizations, Finnish Institute of Occupational Health, Helsinki, Finland Tiina


Paunio * Department of Medical Genetics, University of Helsinki, Helsinki, Finland Teppo Varilo * Department of Psychiatry, Department of Genetics and Development, and Gertrude H. Sergievsky


Center, Columbia University, New York, NY, USA Joseph D. Terwilliger * Division of Medical Genetics, New York State Psychiatric Institute, New York, NY, USA Joseph D. Terwilliger Authors *


Zuzanna Misiewicz View author publications You can also search for this author inPubMed Google Scholar * Tero Hiekkalinna View author publications You can also search for this author


inPubMed Google Scholar * Tiina Paunio View author publications You can also search for this author inPubMed Google Scholar * Teppo Varilo View author publications You can also search for


this author inPubMed Google Scholar * Joseph D. Terwilliger View author publications You can also search for this author inPubMed Google Scholar * Timo Partonen View author publications You


can also search for this author inPubMed Google Scholar * Iiris Hovatta View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS T.Par. and I.H.


designed the study. T.Pau., T.V., T.Par. and I.H. collected the data. Z.M., T.H. and T.Pau. analysed the data. T.H. and J.D.T. assisted with statistical analyses. Z.M. and I.H. wrote the


manuscript. All authors read and commented on the manuscript, and approved the final version. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing financial interests.


RIGHTS AND PERMISSIONS This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the


article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission


from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ Reprints and permissions ABOUT THIS ARTICLE CITE THIS


ARTICLE Misiewicz, Z., Hiekkalinna, T., Paunio, T. _et al._ A genome-wide screen for acrophobia susceptibility loci in a Finnish isolate. _Sci Rep_ 6, 39345 (2016).


https://doi.org/10.1038/srep39345 Download citation * Received: 17 February 2016 * Accepted: 16 November 2016 * Published: 20 December 2016 * DOI: https://doi.org/10.1038/srep39345 SHARE


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