Human Molecular Genetics, 2000, Vol. 9, No. 7 1049-1057
© 2000 Oxford University Press
Genome-wide scan for schizophrenia in the Finnish population: evidence for a locus on chromosome 7q22
1Department of Human Molecular Genetics and 2Department of Mental Health and Alcohol Research, National Public Health Institute, Helsinki, Finland and 3Department of Psychiatry and Columbia Genome Center, Columbia University, New York, NY, USA
Received 9 November 1999; Revised and Accepted 14 February 2000.
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ABSTRACT |
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We report the results of a four-stage genome-wide scan in a schizophrenia study sample consisting of 134 affected sib-pairs collected in Finland. In stage I we genotyped 370 markers from the Weber 6 screening set (N = 52 affected sib-pairs); in stage II we followed up 40 markers by typing first-degree relatives of the sib-pairs; in stage III we genotyped 15 markers in 134 families; and in stage IV we genotyped a denser marker map in the two most promising regions, one on chromosome 1 and another on chromosome 7, in all families. Diagnoses were based on three nationwide health care registers and consensus diagnosis based on review of all medical records. The most significant finding was a two-point lod score of 3.18 with marker D7S486 using a dominant model and treating all individuals with either schizophrenia, schizoaffective disorder or other schizophrenia spectrum disorder as affected. Multipoint analysis with MAPMAKER/SIBS resulted in a MLS of 3.53 between markers D7S501 and D7S523 using the broadest diagnostic model, including major depressive disorder and bipolar type I as affecteds in addition to the aforementioned phenotypes. These results were obtained by including in the analyses only individuals from the late settlement region of Finland settled in the 16th century. Additionally, some support was obtained for linkage to chromosome 1, in a region previously identified in a genome-wide scan of a study sample from a sub-isolate of Finland. Our data demonstrate the importance of genealogical information for studies aiming at identification of predisposing loci in complex diseases.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMaterials and methodsELECTRONIC DATABASE INFORMATIONREFERENCES |
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Schizophrenia, a severe mental disorder affecting approximately one percent of the population worldwide, is a multifactorial disease with a complex mode of inheritance. Several research groups previously have tried to identify susceptibility loci for this debilitating disease, and a number of complete genome scans have also been reported. Evidence for linkage has been reported on several chromosomal regions, including 5q, 6p, 8p, 9, 13q, 18p, 20 and 22q (1). To date, none of these findings has resulted in successful identification of a gene conferring susceptibility to schizophrenia.
When searching for genes behind the common multifactorial disorders, two of the major problems are genetic heterogeneity among affecteds and the polygenic nature of many of these diseases. To circumvent some of these obstacles, we utilized affected sib-pairs from Finland. The Finnish population originates from a limited number of founders (2–4) and has been subsequently rather isolated, leading to increased genetic homogeneity as compared with other larger, more exogamous populations. This population history is likely to be useful in genetic studies of complex disorders.
The genetic epidemiology of schizophrenia has been studied in Finnish twin-pairs (5) leading to an estimate of heritability of 83% in this population. An additional advantage of studying schizophrenia in Finland is the existence of extensive Finnish population registers dating back to the 17th century, which provide an opportunity for rigorous and systematic ascertainment of multiplex families.
Here we report the results of a four-stage genome scan of 134 affected sib-pairs collected throughout Finland. We performed parametric and non-parametric two-point linkage analysis, and additionally employed a multipoint method. Our results provide evidence for linkage to chromosome 7q22, and also lend some additional support for linkage to chromosome 1q32.2–q41, the region identified in another genome-wide scan performed in a study sample rising from an extreme sub-isolate of the late settlement region of Finland (6).
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RESULTS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMaterials and methodsELECTRONIC DATABASE INFORMATIONREFERENCES |
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In stage I, we genotyped 370 polymorphic microsatellite markers from the Weber screening set 6 (7) in 52 affected sib-pairs (104 individuals) without parents. Thirteen markers resulted in lod scores over 0.5 and three markers had dominant or ASP Zmax > 1.0. The highest pairwise lod scores were found for markers D10S2325 (ASP Zmax = 1.87), D5S1473 (ASP Zmax = 1.46), and D14S610 (ASP Zmax = 1.49). The complete list of markers, as well as recessive and dominant affected sib-pair lod scores, are published on our WWW page. On the basis of stage I data we selected markers to be included in stage II.
In stage II we genotyped the 40 markers providing the highest lod scores in stage I in DNA samples of parents or unaffected siblings of the affected sib-pairs. In 19 families we genotyped both parents, in 17 families one parent and one additional sibling, in six families two additional siblings, in one family one additional sibling and no parents, and in 13 families no additional relatives were genotyped. This stage was expected to decrease the likelihood of false positives, and increase the ability to detect genotyping errors that might lead to false negatives (8), providing a more reliable basis for selection of markers to be analyzed in the final stages.
In stage II, 23 markers resulted in affected sib-pair lod scores higher than 0.5, 10 of which were higher than 1.0. The markers providing the highest ASP lod scores were D5S1473 (Zmax = 1.61) and D17S122 (Zmax = 1.60). Results for the remaining markers are available at our WWW site. For stage III we selected the best 15 markers based on the data from stage II.
In stage III, we genotyped an additional set of affected sib-pairs and their first degree relatives, so that the total number of affected sib-pairs was 134. In 44 families we genotyped both parents and no additional siblings, in 23 families one parent and one unaffected sibling, in three families two unaffected siblings and no parents, in four families one parent and no siblings and in seven families no relatives in addition to the affected sib-pair. The diagnoses of the sib-pairs are shown in Table 1. Results for stage III markers are given in Table 2.
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In stage IV we genotyped 29 markers in the two chromosomal regions providing the highest stage III ASP lod scores. These were a 16 cM region around marker D7S1799, which resulted in the highest lod score in stage III (ASP Zmax = 2.42), and a 30 cM region around markers D1S1656 (ASP Zmax = 1.72 in stage III), and D1S2141 for which evidence for linkage was found in another genome scan performed in a study sample from a sub-isolate of Finland (6).
On chromosome 7, the region between markers D7S477 and D7S486 resulted in lod scores up to 2.54 (D7S1799) under diagnostic class 3. A broad ~12 cM peak was observed between the same markers in multipoint analysis using the MAPMAKER/SIBS 0.9 program (9). The highest MLS, 2.62, occurred close to marker D7S1799. Results for the different diagnostic models are presented in Table 3 and Figure 1.
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We incorporated the genealogical data that we had collected on the families into the statistical analyses. When only the families originating from the late settlement region of Finland (3) were included in the analysis, we obtained higher lod scores. Marker D7S486 produced a two-point lod score of 3.18 for the dominant model, and 2.74 for the recessive model under diagnostic class 3, as shown in Table 3. Multipoint analysis using MAPMAKER/SIBS resulted in an MLS of 3.53 between markers D7S501 and D7S523, under the broadest diagnostic model (Fig. 2).
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On chromosome 1 we identified a positive region between markers D1S439 and D1S1656, ~4.1 cM wide on the genetic map, which resulted in lod scores up to 2.62 under the broadest diagnostic model and dominant mode of inheritance. The same region was also implicated by multipoint analysis with MAPMAKER/SIBS with an MLS of 2.51, between markers D1S439 and D1S251 (Fig. 3).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMaterials and methodsELECTRONIC DATABASE INFORMATIONREFERENCES |
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These results based on genotyping of schizophrenic sib-pairs and their relatives from the genetically isolated Finnish population provide evidence for linkage to markers on chromosome 7q22. To our knowledge, no other group has reported significant or suggestive linkage of schizophrenia phenotypes to this chromosomal region. This finding could therefore represent linkage to a novel susceptibility locus, which remains to be confirmed in independent study materials. Interestingly, results of two earlier genome scans would also provide evidence for the involvement of this region. Faraone et al. (10) reported that markers D7S821 and D7S1799 were among the 23 markers giving NPL scores >1.5 (NPL 1.66; 1.74, p-value 0.05; 0.04 respectively) in their study of 43 nuclear families of European–American origin. In the scan reported by Blouin et al. (11), marker D7S2212 gave the fifth most significant evidence for linkage (p = 0.007) out of 452 markers studied in 54 multiplex families of mixed origin. This marker is ~10 cM proximal to the region covered by our dense marker map. It is possible that markers in this region of chromosome 7 provide stronger evidence for linkage in our study sample due to the genetic homogeneity of the Finnish population. The evidence for linkage to chromosome 7 in both two-point and multipoint analyses was observed in markers spanning ~12 cM. Replication of the finding in independent study materials is essential to discern whether this region actually contains a schizophrenia susceptibility gene. No significant evidence for linkage was observed in the regions (e.g. 6p and 8p) for which most of the earlier evidence has accumulated (12).
In comparison with 10 published schizophrenia genome scans, the present two-point lod score of 3.18 is among the most interesting results to date. The most interesting previously published results are those of Pulver et al. (13) on chromosome 8p21–22 in their study of 57 families of mixed origin; Blouin et al. (11) in the same region, and on chromosome 13q32, in a study of 54 families overlapping with the study sample of Pulver et al. (13); Pulver et al. (14) on chromosome 22q12–13.1 in their study of 39 multiplex families; Faraone et al. (10) on chromosome 10 (D10S1423) in a study of 43 families from the NIMH genetics initiative; and Williams et al. (15) on chromosome 10p24. As in most earlier studies, we have used several different tests, in this case four overlapping diagnostic classes, two overlapping tests for linkage and two different sub-divisions of the study sample, and thus the results of potentially interesting regions must be interpreted with caution. The highest lod score in this study was obtained using a sub-set of the data, i.e. the 108 families originating from the late-settlement area of Finland.
It is of interest that we found some evidence for a susceptibility locus on chromosome 1, previously identified in schizophrenia families originating from a sub-isolate in a late settlement area of Finland (6). The marker giving the highest ASP lod score on chromosome 1 in this scan (D1S2833) is ~19.3 cM telomeric from D1S2891, the marker providing the highest lod score in the sub-isolate study, and ~15.4 cM from the distal end of the potential haplotype identified therein. A simulation in an earlier study (16) showed that the most significant evidence for linkage is expected to be observed over an average distance of 7.7 cM (SD 7.2) from the true position of a susceptibility gene because of stochastic variation in sharing at regions away from the disease locus. This simulation assumed analysis of 100 sib-pairs, marker heterozygosity of 0.75, significance levels p = 0.001–0.0001, and five loci each contributing 5% to the variance in an additive manner. Other studies have reached similar conclusions e.g. Roberts et al. (17). It is therefore possible that a susceptibility gene lies between the peaks identified in these two studies but maximal evidence for linkage in the two studies was observed at a slightly different positions due to stochastic variation. The evidence for this assumption is still relatively weak, and the finding would have to be replicated in an even larger sample with a denser set of markers over this region. The interest in this chromosomal region is further justified by a recent report of linkage to markers D1S471–D1S237 on 1q25–q32 in a genome-wide scan for bipolar disorder (18). This region overlaps with the region identified in the present study and in the study by Hovatta et al. (6).
The present results, like those of other genome scans, do not provide any support for one major susceptibility locus significantly increasing the risk of developing schizophrenia. Characteristics of the Finnish population, such as genetic, diagnostic and cultural homogeneity, and the existence of highly reliable registers, may simplify the identification of susceptibility loci with a major impact. This was actually supported by the increased evidence for linkage in the subset representing the young late settlement region (3) of Finland. In this subset a hypothesis of more recently introduced shared genes among affecteds is well justified. It should be emphasized that even in this study sample we did not identify any single significant linkage suggesting one major locus in the genome scan. Most probably several genetic and also environmental factors with a relatively small individual effect contribute to the risk of schizophrenia even in the Finnish population.
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Materials and methods |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMaterials and methodsELECTRONIC DATABASE INFORMATIONREFERENCES |
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Subjects
Probands were identified through three nationwide registers of Finland as described elsewhere (19,20). In total 30 340 schizophrenic patients born between the years 1940 and 1969 were identified. In 1669 families there were two children with schizophrenia, and 409 of these families met our additional criterion of having both parents alive. As greater genetic homogeneity can be expected in the late settlement region (3) of Finland, we targeted the initial sampling efforts to these regions. The majority of the population in the late settlement area originates from a second wave of immigrants in the 16th century, and its genetic diversity is believed to be lower than that of the Finnish population in general (3). Etiological heterogeneity of schizophrenia may be reduced in this sub-sample and therefore a gene having alleles that confer susceptibility to schizophrenia might be easier to identify in this sub-population.
After first contacting the treating personnel, and then the proband, we obtained informed consent and thereafter contacted the rest of the family. Blood samples were taken from affected sib-pairs and their parents. If parents were not alive or if they chose not to participate, we attempted to obtain blood from unaffected siblings. Collection of blood samples was carried out in accordance with the Helsinki declaration, in co-operation with the treating physician most familiar to the proband.
In this genome scan we studied 134 affected sib-pair families with a total of 308 affected individuals, and 242 unaffected parents and/or siblings. The genealogy for 268 of the parents of the affected sib-pairs was traced to the middle of the 19th century, in accordance with published criteria (21), to define their origin more reliably.
Diagnostic assessment
We collected all available psychiatric hospital and outpatient records from all individuals with psychiatric diagnoses in the registers. Records were reviewed independently by two diagnostically trained psychiatrists (J.S., H.J., R.A., M.-L.K.-S.) blind to family structure, and diagnoses were made according to DSM-IV criteria. Whenever two reviewers disagreed on a lifetime diagnosis, consensus was achieved by a third reviewer. Kappa values between the different clinicians that reviewed the diagnostic material were almost perfect for schizophrenia and satisfactory for the other diagnoses. For schizophrenia this was 0.85 (95% CI 0.79–0.92), for schizoaffective disorder 0.73 (95% CI 0.60–0.85), for the schizophrenia spectrum conditions as detailed below (Statistical analysis) it was 0.75 (95% CI 0.59–0.90) and for bipolar I and major depressive disorders 0.69 (95% CI 0.50–0.87).
Diagnostic interviews are usually regarded as an indispensable constituent of the diagnostic process in linkage studies of behavioral phenotypes. Several studies have shown, however, that the accuracy of psychiatric diagnoses in the Finnish Hospital Discharge Register, managed by the free, high quality national health care system in this country, is sufficiently high to be relied on for the purpose of case identification and, in conjunction with review of all available individual medical records, provides a valid best estimate of lifetime psychiatric diagnosis even in the absence of direct interview (22–24). Cannon et al. (5) found 92% agreement (
= 0.84) between a register diagnosis of schizophrenia and an interviewer’s DSM-III-R diagnosis in 72 randomly selected probands and 43 of their siblings born in Helsinki between 1950 and 1958. High specificity of register diagnosis of schizophrenia in the presence of reduced sensitivity indicates that Finnish psychiatrists tend to apply a narrow definition of schizophrenia in their clinical practice. Adding personal interview data to the diagnostic information from registers and medical records would have probably increased sensitivity for schizophrenia spectrum diagnoses, but no crucial additional information could have been expected on siblings with a register diagnosis of schizophrenia supported by review of medical records. Considering only persons with consensus diagnosis based on detailed case note information as affected in linkage analysis, and all others as ‘phenotype unknown’, therefore, seems to be a safe practice where diagnostic interviews are not available.
Laboratory procedures
DNA was extracted from 10 ml EDTA blood according to a standard procedure (25). PCR was performed and PCR products pooled as described elsewhere (26). Gel electrophoresis in stage I of the genome scan was performed on an A.L.F. express automated DNA sequencer (Pharmacia Biotech, Uppsala, Sweden) and genotyping was done by assigning allele numbers according to the fluorescence curves generated. In stages II–IV gel electrophoresis was carried out on an ABI 377 automated DNA sequencer (Perkin Elmer, Foster City, CA), and genotypes were assigned using the Genotyper 2.0 software (Perkin Elmer).
Markers were from Weber screening set 6 (7). Markers that did not work satisfactorily were replaced by markers from the Généthon marker map. A total of 370 polymorphic microsatellite markers on the autosomes and chromosome X (average spacing 10.5 cM) were analyzed in stage I.
Staging of the study
This study has been performed in four stages as follows. In stage I we genotyped 52 affected sib-pairs without any relatives. This was done to minimize the time and cost of genotyping, and provided us with a crude estimate of positive regions. In stage II we genotyped the parents or other first degree relatives of the sib-pairs for the 35 markers giving the highest lod score in stage I. In addition, five markers giving lower lod scores were included for monitoring of the effect of genotyping first degree relatives. This stage was expected to decrease the number of false positives, and therefore provide a better basis for selection of markers to be analyzed further. In stage III we analyzed the 15 markers giving the highest lod scores in stage II on our whole study sample (i.e. 134 affected sib-pairs with parents or other first-degree relatives). Based on the results from stage III we selected the two most interesting regions for further study in stage IV. In stage IV we genotyped a denser marker map for the regions of interest, and analyzed the results using four different diagnostic classes, two different sub-divisions of the study sample, two inheritance models (dominant and recessive) for the two-point analyses and also used a multipoint method (Mapmaker/Sibs). In stage I and II we utilized the first 52 families that had been collected and that met our diagnostic criteria. In stage III and IV we added in families that had been collected later so that the total study sample consisted of 134 families.
Statistical analysis
Since the sample consists primarily of affected siblings and their parents, the maximum number of alleles a sib-pair could share identical-by-descent (IBD) at the disease locus is two. This happens exactly when both parents are informative at the disease locus and transmit the same allele to each of their affected children. The affected-sib-pair mean test tests for deviations from this hypothesis under the assumption that the inheritance of disease alleles from each parent is independent. Knapp et al. (27) demonstrated the statistical equivalence of this sib-pair mean test to linkage analysis under a recessive mode of inheritance assumption with no phenocopies allowed, and infinitesimally rare disease allele (such that both parents would be heterozygous at the disease locus, such that IBD could be inferred in the offspring). As implemented in the SIBPAIR program (28), this has been shown to be one of the more reliable approaches to affected sib-pair analysis, especially when extended to sibships with more than two affecteds (29). This method has been applied to this dataset. This method assumes that segregation from both parents is independent. However, it is also possible to perform the analysis assuming that the sib-pair is sharing alleles IBD from one of the two parents, and not the other. Such an affected relative pair analysis, in which the relative pair are expected to share one allele IBD from one parent, with random segregation from the other has been shown to be equivalent to linkage analysis with a dominant model, rare disease allele, and no phenocopies (30–33), especially on small pedigrees, like the ones analyzed in this study. To this end, such a ‘dominant’ affected relative pair analysis was performed using the MLINK program of the LINKAGE package, with technical details described elsewhere (30–32). Allele frequencies for the markers were estimated from the data itself, under the null hypothesis of no linkage, to be conservative.
In stages one to three we classified individuals either as affected or as unknown. We did not classify anyone as unaffected since we did not ascertain the phenotypic status of individuals not classified as affected in the registers. In stage four we performed two-point analyses for four different diagnostic models. The affected individuals were divided into four increasing inclusive diagnostic classes according to best estimate diagnosis. Diagnostic class 1 included only schizophrenia; class 2 added schizoaffective disorder; class 3 added schizoid, schizotypal and paranoid personality disorders, schizophreniform disorder, delusional disorder, brief psychotic disorder and psychotic disorder NOS; class 4 added major depressive disorder and bipolar I disorder. The syndromes comprising classes 1–3 have consistently been shown to cosegregate in families of probands with schizophrenia, and therefore are usually regarded in linkage studies as members of a schizophrenia spectrum that is based on a common genetic background. On the grounds of Kraepelinian tradition that postulated a different outcome for schizophrenia than for non-psychotic affective disorders, the latter have been assumed also to underlie a different genetic liability than schizophrenia, but two family studies (34,35) have shown that the risk for unipolar depression is increased to the same degree in the first-degree relatives of probands with schizophrenia as it is among the relatives of probands with schizoaffective disorder, bipolar affective disorder, or unipolar depression as compared with relatives of control probands. This finding, though not supported by further family studies (36,37), suggests a common genetic liability for psychotic schizophrenia spectrum conditions and non-psychotic affective disorders that were therefore combined into our broadest diagnostic class 4. Identical analyses were performed considering patients with diagnoses in classes 1, 2, 3 and 4 as affected. In addition we calculated maximum likelihood scores (MLS) using the MAPMAKER/SIBS 0.9 program (9), using the maximum likelihood estimate of IBD sharing alternative under the assumption of dominance variance.
In stage IV, we also analyzed, separately, individuals from the 108 families originating from the northern, more recently inhabited parts of Finland included in the late settlement area as described by Norio et al. (3).
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ACKNOWLEDGEMENTS |
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Dr Alex Parker is acknowledged for his helpful comments on the manuscript. The authors also want to thank Jaana Hartiala, Soili Johansson, Elli Kempas, Mari Sipilä and Anne Vikman for excellent laboratory technical assistance. Liisa Moilanen and Päivi Kortelainen are acknowledged for contacting most of the families. Above all we want to thank the participating schizophrenic patients and their families. This work was supported by Finska Läkaresällskapet r.f., grants from the University of Helsinki and Millenium Pharmaceuticals inc.
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ELECTRONIC DATABASE INFORMATION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMaterials and methodsELECTRONIC DATABASE INFORMATIONREFERENCES |
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National Public Health Institute, Finland, http://www.ktl.fi/molbio/wwwpub/index.html (for results from stages I and II of this study).
Marshfield genetics, http://www.marshfield.org/genetics/ (for information on the Weber 6 screening set).
Généthon, http://www.genethon.fr/genethon_en.html (for information on markers replacing excluded markers from the Weber 6 screening set).
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FOOTNOTES |
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+ Present address: Department of Psychiatry, University of Bonn, Bonn, Germany
§ To whom correspondence should be addressed at present address: Department of Human Genetics, UCLA School of Medicine, Gonda Center, 695 Charles E. Young Drive South, Box 708822, Los Angeles, CA 90095-7088, USA. Tel: +1 310 794 5631; Fax: +1 310 794 5446; Email: lpeltonen@mednet.ucla.edu
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REFERENCES |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMaterials and methodsELECTRONIC DATABASE INFORMATIONREFERENCES |
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