Association Between Genetically Predicted Memory and Self-Reported Foreign Language Proficiency

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Yerdenova, Gaukhar K. Datkhabayeva, Manzura K. Zholdassova, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5601729/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Although contextual variables have a considerable impact on linguistic ability, the effect of genetic factors, especially those linked to memory function, remains poorly understood. The aim of this study was to establish the relationship between genetically determined memory capacity and self-reported foreign language proficiency in 129 children (63 males, 66 females, age 14.2 ± 3.9) and 128 adults (90 males, 38 females, age 29.8 ± 8.2). Seven single nucleotide polymorphisms (SNPs) previously linked with memory function were used in a polygenic analysis ( CAMTA1 rs4908449, CLSTN2 rs6439886, COMT rs4680, CPEB3 rs11186856, SCN1A rs10930201, SNAP25 rs3746544, and WWC1 rs17070145). Self-reported foreign language proficiency was evaluated using a single-item question. Children's level of immersion in foreign languages was divided into three categories: linguistic school, non-linguistic school with extra foreign language courses, and non-linguistic school without additional foreign language courses. We found that genetically predicted memory capacity (i.e., number of memory-increasing alleles) was positively associated with self-reported foreign language proficiency in children ( P = 0.0078) adjusted for age, sex, ethnicity, verbal IQ, and level of immersion in foreign languages. Further, age ( P < 0.0001), level of immersion in foreign languages ( P = 0.0035) and verbal IQ ( P = 0.0004) were also positively associated with self-reported foreign language proficiency in children. The association between genetically predicted memory capacity and self-reported foreign language proficiency was replicated in adults ( P = 0.0158 adjusted for age, sex and ethnicity). In conclusion, foreign language proficiency may partly depend on the presence of a high number of memory-increasing alleles in both children and adults. Genetic markers Intelligence Linguistic immersion Language abilities Cognitive development Behaviour genetics Cognitive abilities Introduction Language proficiency is a complex, diverse, cognitive trait that is crucial for both personality and societal development. Encoding, storing, and retrieving a large quantity of information, such as vocabulary and grammatical rules, is necessary for successful language acquisition (Howard et al. 2012). Language development is influenced by a vast range of variables that interact dynamically over time (De Moor et al. 2018 ) —environment, age, gender, language immersion, culture, socioeconomic level, and intellectual capacity all play a role. Studies have shown a consistent relationship between multilingualism and intellectual capacity: in general, the more languages a person learns, the higher their IQ (Payton et al. 2009). It is reasonable to assume that people with higher intellectual capacity may possess enhanced cognitive abilities that enable them to process, understand, and apply multiple languages more quickly, because language learning is more complex than simply memorizing vocabulary and grammar rules. Although the role of practice within second language learning is widely acknowledged (Thompson et al. 2018), genetics also play a crucial role via hereditary linguistic aptitude (Plomin et al. 2018) — a person's genetic propensity to acquire, and flourish in, language skills. Indeed, intrinsic biological heterogeneity among people has long been acknowledged, with cognitive talents (including language skills) assumed to be among the many phenotypic qualities displaying this variation (Mechelli et al. 2005 ). The connection between memory function and fluency in a foreign language has been of interest to educational psychologists and neurobiologists. Theoretical predictions suggest that genetics may predict not just memory capacity but also second language acquisition ability. Genetic variables impacting memory function have also been explored. The idea that genes have a role in memory is not new; in fact, it goes back to the middle of the 20th century, when researchers first began looking at how genes affect human cognition (Plomin et al. 2004). Twin studies have provided strong evidence that individual variations in memory function are mostly caused by genetic variation (Posthuma et al. 2000). Different facets of memory functioning have been linked to genes, including COMT and APOE , among others (Papassotiropoulos et al. 2011). Early studies looking at the relationship between memory, heredity, and learning a foreign language mostly focused on dyslexia and other learning difficulties (Kere et al. 2014). Language acquisition is often challenging for people with dyslexia, something which has been linked in part to hereditary memory-affecting variables (Pennington et al. 2006). By the 21st century, however, improvements in genetic analysis methods made it possible for researchers examine these connections on a genome-wide scale (Visscher et al. 2017 ). One might hypothesize that if some genetic markers predict memory function, they would also influence a person's capacity to learn a new language. Thus, in the first study of its type, we aimed to establish the relationship between genetically determined memory capacity and self-reported foreign language proficiency in two cohorts of children and adults. Material and Methods Ethics Statement The Ethics Committees of the Al-Farabi Kazakh National University (Approval numbers: IRB-A172 and IRB-A267) and the Federal Research and Clinical Center of Physical-Chemical Medicine of the Federal Medical and Biological Agency of Russia (Approval number 2017/04) approved the protocols for the research. Informed consent was obtained from all participants (and parents or legal guardians, where appropriate) involved in the study. The study was conducted according to the guidelines of the Declaration of Helsinki and Strengthening The Reporting of Genetic Association Studies (STREGA): An extension of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement recommendations. Participants The first cohort comprised 129 healthy children (63 males, 66 females; 111 Kazakhs, 18 Russians; age 14.2 ± 3.9; age range 7-21) from Kazakhstan. The children attended different schools, where the first language was either Kazakh (n=63) or Russian (n=66). The pupils either went to a school with in-depth study of foreign languages (linguistic), a non-linguistic school that offered extra courses in foreign languages, or a non-linguistic school that did not provide extra courses in foreign languages. Because it was expected that the amount of immersion in foreign languages may have an effect on language competency, the design of the research took into consideration the distribution of pupils throughout these different kinds of schools. The second cohort comprised 128 healthy adults (90 males, 38 females; 107 Russians, 21 Ukrainians and Belarusians; age 29.8 ± 8.2; age range 18-54) from Russia. Russians, Belarusians and Ukrainians belong to the East Slavic group of Eastern Europeans. This cohort was previously described in detail (Hall et al. 2021), and a portion of that cohort had agreed to answer questions about foreign language proficiency. Psychometric Methods To determine engagement with foreign languages and foreign language proficiency, participants (in conjunction with their parents where appropriate) were asked to respond to questions regarding (a) what second languages they spoke (open-ended), (b) their level of immersion in foreign languages (for children only: linguistic school, non-linguistic school with extra foreign language courses, and non-linguistic school without additional foreign language courses; coded as 3,2,1, respectively), and (c) their self-reported level of foreign language proficiency (rated as beginner, elementary, intermediate, or advanced—coded as 1, 2, 3, or 4, respectively). For most participants, their second (foreign) language was English (128 children and 124 adults); for four participants their second language was German; and for one participant, their second language was French. Intelligence was measured in children only using the Wechsler test, which includes 11 separate component sub-tests across six verbal and five non-verbal aspects. The study used two versions of the Wechsler test for two age categories of participants: (a) 7-15 years old: Wechsler Intelligence Scale for Children (WISC) test—for testing children and adolescents (Wechsler 1949). The children's version of this test was adapted and standardized for Russian speakers by A. Yu. Panasyuk (Panasyk 1973). (b) 16-21 years old: Wechsler Adult Intelligence Scale (WAIS) test—designed to test adults (Wechsler 1955). This version was adapted and standardized for Russian speakers by A. Yu. Panasyuk, and supplemented and corrected by Yu. I. Filimonenko and V. I. Timofeev at the State Enterprise "Imaton", St. Petersburg (Panasyk 1992). Both intelligence test versions were translated into the Kazakh language for those children for whom the Kazakh language was their first language. Cronbach’s alpha internal consistency reliability for the intelligence tests within the present samples are shown in Table 1. Table 1. Cronbach's alpha for the Kazakh and Russian versions of Wechsler Intelligence Scales Tests Language Cronbach's alpha Wechsler Intelligence Scale for Children General Kazakh 0.75 Russian 0.82 Verbal Kazakh 0.71 Russian 0.77 Nonverbal Kazakh 0.66 Russian 0.68 Wechsler Adult Intelligence Scale General Kazakh 0.83 Russian 0.83 Verbal Kazakh 0.78 Russian 0.77 Nonverbal Kazakh 0.67 Russian 0.72 Genetic Analysis In this study, seven key genetic markers that are connected with memory capacity were selected and genotyped in the studied samples (Table 2). Table 2. List of selected genetic markers associated with memory Gene Polymorphism Alleles Favorable allele References CAMTA1 rs4908449 T/C T Huentelman et al., 2007 CLSTN2 rs6439886 A/G G Papassotiropoulos et al., 2006; Preuschhof et al., 2010; Laukka et al., 2020 COMT rs4680 G/A A Aguilera et al., 2008; Miskowiak et al., 2017; Sugiura et al., 2017; Dumontheil et al., 2019 CPEB3 rs11186856 A/G A Vogler et al., 2009 SCN1A rs10930201 A/C A Papassotiropoulos et al., 2011 SNAP25 rs3746544 G/T G Wang et al., 2018 WWC1 rs17070145 C/T T Papassotiropoulos et al., 2006; Preuschhof et al., 2009; Milnik et al., 2012; Zlomuzica et al., 2018; Stickel et al., 2018; Laukka et al., 2020 Genetic markers were selected based on reproducibility of results, sample size of each study, and methodology (some markers were discovered in the genome-wide association studies, such as CLSTN2 rs6439886, SCN1A rs10930201, and WWC1 rs17070145). Genotyping of children’s DNA samples Samples were collected using a non-invasive method of sampling the epithelium of cells from the oral cavity of the 129 participants. DNA was extracted from the buccal swab samples using a QIAamp DNA Mini kit (Cat No. 51306; Qiagen, Germany) according to the manufacturer’s instructions. Samples were processed as previously described (Ahmetov et al. 2023). Genomic DNA quantity and quality were assessed using a Nanodrop2000 spectrophotometer (Thermo Scientific, Massachusetts, USA). In silico primers design was performed to cover the seven selected SNPs. The primer sequences used for genotyping are listed in Table 3. Table 3. List of primers used for the targeted next-generation sequencing Gene Poly-morphism Forward Primer Sequence Reverse Primer Sequence CAMTA1 rs4908449 TTATTGGCCTATCTCCTTGCT GAGAAAGATGGGCGGAGAG CLSTN2 rs6439886 GGAAGAGGGGCAGAGATTG TGAAACTGACAGTCGGCACA COMT rs4680 GAGATCAACCCCGACTGTG CTGGTGGGGAGGACAAAGT CPEB3 rs11186856 TGCTGTTTGACTTGGGTGGT CTAAATTCAAGGATCAAGGGG SCN1A rs10930201 TGTTATCTACTTTCTGTTACTTG CTTCTCTTGGCTAATTGTCTTA SNAP25 rs3746544 ACACACATCAGTCCACCCC AACAGCACATTGAGCATTCCT WWC1 rs17070145 TACTCCCAGCACACACCTC GTTGGCAGATGGAACCCGT First, the primers were evaluated using control DNA samples, and the expected PCR product size was validated using agarose gel electrophoresis. Next, the primers were tagged with Fluidigm-specific tag sequences CS1: ACACTGACGACATGGTTCTACA for the forward’s primer, and CS2: TACGGTAGCAGAGACTTGGTCT for the reverse’s primer. The libraries for DNA sequencing using the Fluidigm Access Array microfluidic chip were generated as previously described (Gouda et al. 2022). Samples were pooled and sequenced using the Ion 520™ Chip on the Ion S5 XL Semiconductor sequencer following the manufacturer’s instructions (Thermo Fischer). The genomic data were treated using an in-house bioinformatics pipeline, including alignment to the reference genome GRCh37/hg19, quality control assessment, SNP calling, and variant annotation as previously described (Jalaleddine et al. 2022). SNP genotyping of the seven studied markers was collected for all samples. The Functional annotation of the variants was performed using the Ensembl Variant Effect Predictor tool (McLaren et al. 2016). Genotyping of adults’ DNA samples Molecular genetic analysis was performed with DNA samples obtained from leukocytes (venous blood). Four ml of venous blood were collected in tubes containing EDTA (Vacuette EDTA tubes, Greiner Bio-One, Kremsmünster, Austria). DNA extraction and purification were performed using a commercial kit according to the manufacturer’s instructions (Technoclon, Moscow, Russia). HumanOmniExpressBeadChips (Illumina Inc., San Diego, CA, USA) were used to genotype seven polymorphisms, as previously described (Boulygina et al. 2020). Statistical Analyses Statistical analyses were conducted using GraphPad InStat (GraphPad Software, Inc., San Diego, CA, USA) software. Multiple regression analyses were used to assess the relationships between self-reported foreign language proficiency and genetically predicted memory capacity (number of favourable alleles from 0 to 14) and all other variables (sex, age, ethnicity, verbal IQ, and level of immersion in foreign languages for children; sex, age, and ethnicity, for adults), and to determine the combined association ( R 2 —the percentage of variance in self-reported foreign language proficiency) of individual factors adjusted for covariates. All data are presented as mean (SD). P values < 0.05 were considered statistically significant. Results The genotype distribution and allelic frequencies of the seven SNPs linked to memory function in the two cohorts are shown in Table 4 . The number of memory-increasing (favourable) alleles (minimum – 0, maximum – 14) ranged from 2 to 10 for children, and from 2 to 11 for adults. Table 4 Genotype and allele frequencies of 7 memory-related SNPs in children (n = 129) and adults (n = 128). Polymorphism Genotype 1 Genotype 2 Genotype 3 Memory-increasing allele frequency, % Children CAMTA1 rs4908449 TT (20) TC (49) CC (60) T (34.5) CLSTN2 rs6439886 GG (0) AG (19) AA (110) G (7.4) COMT rs4680 AA (18) GA (19) GG (92) A (21.3) CPEB3 rs11186856 AA (107) AG (19) GG (3) A (90.3) SCN1A rs10930201 AA (39) AC (1) CC (89) A (30.6) SNAP25 rs3746544 GG (11) GT (67) TT (51) G (34.5) WWC1 rs17070145 TT (42) CT (67) CC (20) T (58.5) Adults CAMTA1 rs4908449 TT (25) TC (46) CC (57) T (37.5) CLSTN2 rs6439886 GG (2) AG (30) AA (96) G (13.3) COMT rs4680 AA (32) GA (70) GG (26) A (52.3) CPEB3 rs11186856 AA (69) AG (49) GG (10) A (73.0) SCN1A rs10930201 AA (56) AC (62) CC (10) A (68.0) SNAP25 rs3746544 GG (17) GT (57) TT (54) G (35.5) WWC1 rs17070145 TT (20) CT (59) CC (49) T (38.7) Sex had no significant effect on any of the tested variables of the children, including verbal IQ ( P = 0.402), self-reported foreign language proficiency ( P = 0.486), level of immersion in foreign languages ( P = 0.756) and number of memory-increasing alleles ( P = 0.312). Furthermore, there were no significant differences in the number of memory-increasing alleles between Kazakhs and Russians living in Kazakhstan. We therefore felt justified to combine all participants into one group for further analyses. In children, we found that genetically predicted memory capacity (number of memory-increasing alleles) was positively associated with self-reported foreign language proficiency ( β = 0.108, P = 0.0048, adjusted for age, sex, ethnicity, verbal IQ, and level of immersion in foreign languages). Furthermore, age ( β = 0.09; P < 0.0001), level of immersion in foreign languages ( β = 0.3; P = 0.0026) and verbal IQ ( β = 0.02; P = 0.0006) were also positively associated with children’s self-reported foreign language proficiency. When combined, genetically predicted memory capacity, age, sex, ethnicity, verbal IQ, and level of immersion in foreign languages explained 32% ( P < 0.0001) of the variance in children’s self-reported foreign language proficiency. In adults, age ( P = 0.180), sex ( P = 0.149), and ethnicity ( P = 0.799) had no effect on self-reported foreign language proficiency. Furthermore, there were no significant differences in the number of memory-increasing alleles between Russians and the other two East Slavic ethnic groups (Belarusians and Ukrainians). We therefore felt justified to combine all participants into one group for further analyses. The positive association between genetically predicted memory capacity and self-reported foreign language proficiency was replicated in adults ( P = 0.0158 adjusted for age, sex and ethnicity). Discussion To the best of our knowledge, this is the first study to show that genetically determined memory capacity is positively associated with self-reported foreign language proficiency. Alongside this key finding, we demonstrated that age, level of immersion in foreign languages, and verbal IQ were also positively associated with self-reported foreign language proficiency. Of particular note, we were able to replicate our findings in children with a separate sample of adults. Our study was based on a body of past research showing that multiple cognitive skills, including working memory, are important for effective language learning (Mechelli et al. 2005 ). Seven genetic variants used in our research have previously been linked to memory and other cognitive-related traits, such as spatial ability, intelligence and educational attainment. These variants are located in genes ( CAMTA1 , CLSTN2 , COMT , CPEB3 , SCN1A , SNAP25 , and WWC1 ) responsible for neurological processes that underlie memory and cognitive function, including synaptic plasticity, neurogenesis, and neurotransmission. The CAMTA1 gene encodes calmodulin-binding transcription activator 1, which interfaces with the calcium-calmodulin system of the cell to alter gene expression patterns (Huentelman et al. 2007 ). Carriers of the CAMTA1 rs4908449 T allele have been shown to demonstrate better performance in an episodic recall memory test (Huentelman et al. 2007 ). The CLSTN2 gene encodes calsyntenin 2, and is involved in positive regulation of synapse assembly and positive regulation of synaptic transmission (Preuschhof et al. 2010 ). Carriers of the CLSTN2 rs6439886 G allele have better episodic memory (Preuschhof et al. 2010 ; Papassotiropoulos et al. 2006 ; Laukka et al. 2020 ). The COMT gene encodes catechol-O-methyltransferase, which catalyzes the transfer of a methyl group from S-adenosylmethionine to catecholamines, including the neurotransmitters dopamine, epinephrine, and norepinephrine. The COMT rs4680 A allele has been reported to be associated with better verbal working memory (Aguilera et al. 2008 ), language ability (Sugiura et al. 2017 ), spatial working memory (Miskowiak et al. 2017 ), and visuospatial and social working memory (Dumontheil et al. 2020 ). The CPEB3 gene encodes cytoplasmic polyadenylation element binding protein 3, which is crucial for synaptic plasticity and memory in model organisms (Dumontheil et al. 2020 ). The CPEB3 rs11186856 A allele is associated with episodic memory (Vogler et al. 2009 ). The SCN1A gene encodes sodium voltage-gated channel alpha subunit 1 and regulates the release of neurotransmitters in neurons. The SCN1A rs10930201 A allele has been linked with short-term memory (Papassotiropoulos et al. 2011). The SNAP25 gene encodes synaptosome associated protein 25, which plays an important role in the synaptic function of specific neuronal systems. The SNAP25 rs3746544 G allele has been reported to be associated with better brain functional connectivity density and working memory (Wang et al. 2018 ). The WWC1 (also known as KIBRA ) gene encodes WW and C2 domain containing 1 protein, which together with its binding partners (dendrin, synaptopodin, dynein-complex, and others) plays an important role in synaptic plasticity (18). The WWC1 gene rs17070145 T allele has been linked with better episodic and working memory (Ahmetov et al. 2023 ; Preuschhof et al. 2010 ; Milnik et al. 2012 ; Zlomuzica et al. 2018 ; Laukka et al. 2020 ) and verbal memory (Stickel et al. 2018 ). Against the backdrop of this study’s novel findings, there are some limitations that should be acknowledged. First, our cohort of children was heterogeneous with respect to age, ethnicity and level of immersion in foreign languages. We therefore adjusted our findings for these and other (sex and verbal IQ) covariates. Second, to test foreign language proficiency, we used a self-reported phenotype (a survey question), which was swift to administer, but we acknowledge the availability of various objective assessments of foreign language proficiency (e.g., TOEFL, IELTS, etc.). Finally, our study is limited to the seven common polymorphisms which were primarily selected because of previously reported associations with memory capacity. It is likely, however, that future research will show that many additional common polymorphisms, and probably rare mutations as well, are associated with memory capacity and foreign language proficiency. Overall, our research provides strong support for the idea that memory function and linguistic abilities are genetically linked. Indeed, the present study suggests that self-reported foreign language proficiency may partly depend on the presence of a high number of memory-increasing alleles in both children and adults. The process behind genetically predicted memory capacity and self-reported foreign language proficiency needs to be further investigated in order to develop individualized teaching methods and interventions targeted at enhancing language learning results. This study also highlights that researchers examining cognitive variables and educational policy-makers would be well-advised to consider taking into account the influence of genetic variables, especially with regard to memory and language development. Declarations Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding The Kazakhstan part of the study was funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. BR27198099). Author Contribution MBY: formal analysis, investigation, writing – original draft; GKD: formal analysis, investigation; MKZ: investigation; ATK: investigation; ZMS: investigation; AB: investigation; PMB: investigation; RH: investigation; EAS: formal analysis; AKL: investigation; NAK: formal analysis; EVG: investigation, resources, project administration; TR: formal analysis, writing – review & editing; AMK: conceptualization, supervision, funding acquisition, methodology, resources, project administration (PI), writing – review & editing; IIA: conceptualization, formal analysis, methodology, writing – original draft. All authors contributed to the article and approved the submitted version. Data Availability The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. References Aguilera M, Barrantes-Vidal N, Arias B, Moya J, Villa H, Ibáñez MI, Ruipérez MA, Ortet G, Fañanás L (2008) Putative role of the COMT gene polymorphism (Val158Met) on verbal working memory functioning in a healthy population. Am J Med Genet B Neuropsychiatr Genet 147B:898–902. https://doi.org/10.1002/ajmg.b.30705 Ahmetov II, Valeeva EV, Yerdenova MB, Datkhabayeva GK, Bouzid A, Bhamidimarri PM, Sharafetdinova LM, Egorova ES, Semenova EA, Gabdrakhmanova LJ, Yusupov RA, Larin AK, Kulemin NA, Generozov EV, Hamoudi R, Kustubayeva AM, Rees T (2023) KIBRA gene variant is associated with ability in chess and science. Genes 14:204. https://doi.org/10.3390/genes14010204 Boulygina EA, Borisov OV, Valeeva EV, Semenova EA, Kostryukova ES, Kulemin NA, Larin AK, Nabiullina RM, Mavliev FA, Akhatov AM, Andryushchenko ON, Andryushchenko LB, Zmijewski P, Generozov EV, Ahmetov II (2020) Whole genome sequencing of elite athletes. Biol Sport 37(3):295–304. https://doi.org/10.5114/biolsport.2020.96272 De Moor SAG, De Kort MHM, Boomsma DI (2018) Biochemical genetics of human memory. Psychon Bull Rev 25:187–202 Dumontheil I, Kilford EJ, Blakemore SJ (2020) Development of dopaminergic genetic associations with visuospatial, verbal and social working memory. Dev Sci 23(2):e12889. https://doi.org/10.1111/desc.12889 Gouda HR, Talaat IM, Bouzid A, El-Assi H, Nabil A, Venkatachalam T, Manasa Bhamidimarri P, Wohlers I, Mahdami A, El-Gendi S, ElKoraie A, Busch H, Saber-Ayad M, Hamoudi R, Baddour N (2022) Genetic analysis of CFH and MCP in Egyptian patients with immune-complex proliferative glomerulonephritis. Front Immunol 13:960068. https://doi.org/10.3389/fimmu.2022.960068 Hall ECR, Semenova EA, Bondareva EA, Borisov OV, Andryushchenko ON, Andryushchenko LB, Zmijewski P, Generozov EV, Ahmetov II (2021) Association of muscle fiber composition with health and exercise-related traits in athletes and untrained subjects. Biol Sport 38:659–666. https://doi.org/10.5114/biolsport.2021.102923 Howard HC, Borry P (2012) Is there a doctor in the house? The presence of physicians in the direct-to-consumer genetic testing context. J Community Genet 3(2):105–112. https://doi.org/10.1007/s12687-011-0062-0 Huentelman MJ, Papassotiropoulos A, Craig DW, Hoerndli FJ, Pearson JV, Huynh KD, Corneveaux J, Hänggi J, Mondadori CR, Buchmann A, Reiman EM, Henke K, de Quervain DJ, Stephan DA (2007) Calmodulin-binding transcription activator 1 (CAMTA1) alleles predispose human episodic memory performance. Hum Mol Genet 16(12):1469–1477. https://doi.org/10.1093/hmg/ddm097 Jalaleddine N, Bouzid A, Hachim M, Sharif-Askari NS, Mahboub B, Senok A, Halwani R, Hamoudi RA, Al Heialy S (2022) ACE2 polymorphisms impact COVID-19 severity in obese patients. Sci Rep 12(1):21491. https://doi.org/10.1038/s41598-022-26072-7 Kere J (2014) The molecular genetics and neurobiology of developmental dyslexia as model of a complex phenotype. Biochem Biophys Res Commun 452(2):236–243. https://doi.org/10.1016/j.bbrc.2014.07.102 Laukka EJ, Köhncke Y, Papenberg G, Fratiglioni L, Bäckman L (2020) Combined genetic influences on episodic memory decline in older adults without dementia. Neuropsychology 34(6):654–666. https://doi.org/10.1037/neu0000637 McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, Flicek P, Cunningham F (2016) The Ensembl Variant Effect Predictor. Genome Biol 17(1):122. https://doi.org/10.1186/s13059-016-0974-4 Mechelli A, Price CJ, Friston KJ, Ashburner R (2005) Voxel-based morphometry of the human brain: Methods and applications. Curr Med Imag Rev 1:105–113 Milnik A, Heck A, Vogler C, Heinze HJ, de Quervain DJ, Papassotiropoulos A (2012) Association of KIBRA with episodic and working memory: A meta-analysis. Am J Med Genet B Neuropsychiatr Genet 159(8):58–69. https://doi.org/10.1002/ajmg.b.32101 Miskowiak KW, Kjaerstad HL, Støttrup MM, Svendsen AM, Demant KM, Hoeffding LK, Werge TM, Burdick KE, Domschke K, Carvalho AF, Vieta E, Vinberg M, Kessing LV, Siebner HR, Macoveanu J (2017) The catechol-O-methyltransferase (COMT) Val158Met genotype modulates working memory-related dorsolateral prefrontal response and performance in bipolar disorder. Bipolar Disord 19(3):214–224. https://doi.org/10.1111/bdi.12497 Panasyk A (1973) Adaptirovannyi variant metodiki D. Vekslera (WISC) (Adapted version of the methodology of D. Veksler (WISC)). Institute of Hygiene of Children and Adolescents of the USSR Ministry of Health Panasyk A, Filimonenko Y, Timofeev V (1992) Rukovodstvo k metodike issledovaniya intellekta u detei D. Veksler (Guide to the methodology of the study of intelligence in children by D. Wexler). State Enterprise IMATON Papassotiropoulos A, de Quervain DJ (2011) Genetics of human episodic memory: Dealing with complexity. Trends Cogn Sci 15(9):381–387. https://doi.org/10.1016/j.tics.2011.07.005 Papassotiropoulos A, Stephan DA, Huentelman MJ, Hoerndli FJ, Craig DW, Pearson JV, Huynh KD, Brunner F, Corneveaux J, Osborne D, Wollmer MA, Aerni A, Coluccia D, Hänggi J, Mondadori CR, Buchmann A, Reiman EM, Caselli RJ, Henke K, de Quervain DJ (2006) Common Kibra alleles are associated with human memory performance. Science 314(5798):475–478. https://doi.org/10.1126/science.1129837 Payton ES (2009) The impact of genetic research on our understanding of normal cognitive ageing: 1995 to 2009. Neuropsychol Rev 19:451–477. https://doi.org/10.1007/s11065-009-9116-z Pennington BF (2006) From single to multiple deficit models of developmental disorders. Cognition 101(2):385–413. https://doi.org/10.1016/j.cognition.2006.04.008 Plomin R, Spinath FM (2004) Intelligence: Genetics, genes, and genomics. J Pers Soc Psychol 86(1):112–129. https://doi.org/10.1037/0022-3514.86.1.112 Plomin R, Von Stumm S (2018) The new genetics of intelligence. Nat Rev Genet 19:148–159. https://doi.org/10.1038/nrg.2017.104 Posthuma D, Boomsma DI (2000) A note on the statistical power in extended twin designs. Behav Genet 30(2):147–158. https://doi.org/10.1023/a:1001959306025 Preuschhof C, Heekeren HR, Li SC, Sander T, Lindenberger U, Bäckman L (2010) KIBRA and CLSTN2 polymorphisms exert interactive effects on human episodic memory. Neuropsychologia 48(2):402–408. https://doi.org/10.1016/j.neuropsychologia.2009.09.031 Stickel A, Kawa K, Walther K, Glisky E, Richholt R, Huentelman M, Ryan L (2018) Age-modulated associations between KIBRA, brain volume, and verbal memory among healthy older adults. Front Aging Neurosci 10:431. https://doi.org/10.3389 Sugiura L, Toyota T, Matsuba-Kurita H, Iwayama Y, Mazuka R, Yoshikawa T, Hagiwara H (2017) Age-dependent effects of catechol-O-methyltransferase (COMT) gene Val158Met polymorphism on language function in developing children. Cereb Cortex 27(1):104–116. https://doi.org/10.1093/cercor/bhw371 Thompson C (2018) The role of practice within second language acquisition. In: Jones C (ed) Practice in second language learning. Cambridge University Press, pp 30–52. https://doi.org/10.1017/9781316443118.004 Visscher PM, Wray NR, Zhang Q, Sklar P, McCarthy MI, Brown MA, Yang J (2017) 10 years of GWAS discovery: Biology, function, and translation. Am J Hum Genet 101(1):5–22. https://doi.org/10.1016/j.ajhg.2017.06.005 Vogler C, Spalek K, Aerni A, Demougin P, Müller A, Huynh KD, Papassotiropoulos A, de Quervain DJ (2009) CPEB3 is associated with human episodic memory. Front Behav Neurosci 3:4. https://doi.org/10.3389/neuro.08.004.2009 Wang C, Yang B, Fang D, Zeng H, Chen X, Peng G, Cheng Q, Liang G (2018) The impact of SNAP25 on brain functional connectivity density and working memory in ADHD. Biol Psychol 138:35–40. https://doi.org/10.1016/j.biopsycho.2018.08.005 Wechsler D (1949) Wechsler intelligence scale for children. The Psychological Corporation Wechsler D (1955) Manual for the Wechsler Adult Intelligence Scale. The Psychological Corporation Zlomuzica A, Preusser F, Roberts S, Woud ML, Lester KJ, Dere E, Eley TC, Margraf J (2018) The role of KIBRA in reconstructive episodic memory. Mol Med 24(1):7. https://doi.org/10.1186/s10020-018-0007-8 Additional Declarations No competing interests reported. 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Datkhabayeva","email":"","orcid":"","institution":"Al-Farabi Kazakh National University","correspondingAuthor":false,"prefix":"","firstName":"Gaukhar","middleName":"K.","lastName":"Datkhabayeva","suffix":""},{"id":429619486,"identity":"40c7aa2c-2b8e-49dd-93c6-a6bbb24cb240","order_by":2,"name":"Manzura K. Zholdassova","email":"","orcid":"","institution":"Al-Farabi Kazakh National University","correspondingAuthor":false,"prefix":"","firstName":"Manzura","middleName":"K.","lastName":"Zholdassova","suffix":""},{"id":429619487,"identity":"46d917a0-7bd3-4f8c-884d-4b98a56be95c","order_by":3,"name":"Altyngul T. Kamzanova","email":"","orcid":"","institution":"Al-Farabi Kazakh National University","correspondingAuthor":false,"prefix":"","firstName":"Altyngul","middleName":"T.","lastName":"Kamzanova","suffix":""},{"id":429619488,"identity":"be703849-6570-4bb2-b13b-04bcd0f4f119","order_by":4,"name":"Zukhra M. 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Kulemin","email":"","orcid":"","institution":"Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency","correspondingAuthor":false,"prefix":"","firstName":"Nikolay","middleName":"A.","lastName":"Kulemin","suffix":""},{"id":429619501,"identity":"bafd8735-6c4d-4a56-964b-d1d958964d29","order_by":11,"name":"Edward V. Generozov","email":"","orcid":"","institution":"Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency","correspondingAuthor":false,"prefix":"","firstName":"Edward","middleName":"V.","lastName":"Generozov","suffix":""},{"id":429619502,"identity":"76cb4156-9eb1-4c1e-9279-a7bde3417795","order_by":12,"name":"Tim Rees","email":"","orcid":"","institution":"Bournemouth University","correspondingAuthor":false,"prefix":"","firstName":"Tim","middleName":"","lastName":"Rees","suffix":""},{"id":429619503,"identity":"aec4e193-9014-422e-b316-285eaf341147","order_by":13,"name":"Almira M. Kustubayeva","email":"","orcid":"","institution":"Al-Farabi Kazakh National University","correspondingAuthor":false,"prefix":"","firstName":"Almira","middleName":"M.","lastName":"Kustubayeva","suffix":""},{"id":429619504,"identity":"4fed3727-f768-4aaf-a554-56d0021c6251","order_by":14,"name":"Ildus I. Ahmetov","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIie3RMQrCMBSA4SeBuLR2TRDsFSKZiuJZlIIudRB3EQS79AD1FoKQOZLBpe66VbyA4AE0WsVOsaNg/imEfPAeAbDZfjAMgFBxRFtJXre1eQWiH+N+NQIf4jD5vjKSBqAzn0TdmUeiiwwiBV4sMU2Ng2EersSQ0HS8llQoIFkf07V5F65coQjL9gWBA2CaG0n9qslNkyx/Ev87cXjoCknYLoEnYQ9iHAw5U+6KkK7iJdNk5LSzwSIwre/H8abpip7nIXQ6U9FptXZqe0wMBFD5/Pid7x9Zrnap/tZms9n+qDvT9EZy02vJZAAAAABJRU5ErkJggg==","orcid":"","institution":"Liverpool John Moores University","correspondingAuthor":true,"prefix":"","firstName":"Ildus","middleName":"I.","lastName":"Ahmetov","suffix":""}],"badges":[],"createdAt":"2024-12-08 07:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5601729/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5601729/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78721170,"identity":"d9fd48b0-33d5-4dc2-8b30-285746bea93d","added_by":"auto","created_at":"2025-03-18 04:48:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":767704,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5601729/v1/bcf8369e-9911-4275-82cf-981a6e5b1c84.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Genetically Predicted Memory and Self-Reported Foreign Language Proficiency","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLanguage proficiency is a complex, diverse, cognitive trait that is crucial for both personality and societal development. Encoding, storing, and retrieving a large quantity of information, such as vocabulary and grammatical rules, is necessary for successful language acquisition (Howard et al. 2012). Language development is influenced by a vast range of variables that interact dynamically over time (De Moor et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) \u0026mdash;environment, age, gender, language immersion, culture, socioeconomic level, and intellectual capacity all play a role. Studies have shown a consistent relationship between multilingualism and intellectual capacity: in general, the more languages a person learns, the higher their IQ (Payton et al. 2009). It is reasonable to assume that people with higher intellectual capacity may possess enhanced cognitive abilities that enable them to process, understand, and apply multiple languages more quickly, because language learning is more complex than simply memorizing vocabulary and grammar rules.\u003c/p\u003e \u003cp\u003eAlthough the role of practice within second language learning is widely acknowledged (Thompson et al. 2018), genetics also play a crucial role via hereditary linguistic aptitude (Plomin et al. 2018) \u0026mdash; a person's genetic propensity to acquire, and flourish in, language skills. Indeed, intrinsic biological heterogeneity among people has long been acknowledged, with cognitive talents (including language skills) assumed to be among the many phenotypic qualities displaying this variation (Mechelli et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe connection between memory function and fluency in a foreign language has been of interest to educational psychologists and neurobiologists. Theoretical predictions suggest that genetics may predict not just memory capacity but also second language acquisition ability. Genetic variables impacting memory function have also been explored. The idea that genes have a role in memory is not new; in fact, it goes back to the middle of the 20th century, when researchers first began looking at how genes affect human cognition (Plomin et al. 2004). Twin studies have provided strong evidence that individual variations in memory function are mostly caused by genetic variation (Posthuma et al. 2000). Different facets of memory functioning have been linked to genes, including \u003cem\u003eCOMT\u003c/em\u003e and \u003cem\u003eAPOE\u003c/em\u003e, among others (Papassotiropoulos et al. 2011).\u003c/p\u003e \u003cp\u003eEarly studies looking at the relationship between memory, heredity, and learning a foreign language mostly focused on dyslexia and other learning difficulties (Kere et al. 2014). Language acquisition is often challenging for people with dyslexia, something which has been linked in part to hereditary memory-affecting variables (Pennington et al. 2006). By the 21st century, however, improvements in genetic analysis methods made it possible for researchers examine these connections on a genome-wide scale (Visscher et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne might hypothesize that if some genetic markers predict memory function, they would also influence a person's capacity to learn a new language. Thus, in the first study of its type, we aimed to establish the relationship between genetically determined memory capacity and self-reported foreign language proficiency in two cohorts of children and adults.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003ch2\u003eEthics Statement\u003c/h2\u003e\n\u003cp\u003eThe Ethics Committees of the Al-Farabi Kazakh National University (Approval numbers: IRB-A172 and IRB-A267) and the Federal Research and Clinical Center of Physical-Chemical Medicine of the Federal Medical and Biological Agency of Russia (Approval number 2017/04) approved the protocols for the research. Informed consent was obtained from all participants (and parents or legal guardians, where appropriate) involved in the study. The study was conducted according to the guidelines of the Declaration of Helsinki and Strengthening The Reporting of Genetic Association Studies (STREGA): An extension of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement recommendations.\u003c/p\u003e\n\u003ch2\u003eParticipants\u003c/h2\u003e\n\u003cp\u003eThe first cohort comprised 129 healthy children (63 males, 66 females; 111 Kazakhs, 18 Russians; age 14.2 \u0026plusmn; 3.9; age range 7-21) from Kazakhstan. The children attended different schools, where the first language was either Kazakh (n=63) or Russian (n=66). The pupils either went to a school with in-depth study of foreign languages (linguistic), a non-linguistic school that offered extra courses in foreign languages, or a non-linguistic school that did not provide extra courses in foreign languages. Because it was expected that the amount of immersion in foreign languages may have an effect on language competency, the design of the research took into consideration the distribution of pupils throughout these different kinds of schools.\u003c/p\u003e\n\u003cp\u003eThe second cohort comprised 128 healthy adults (90 males, 38 females; 107 Russians, 21 Ukrainians and Belarusians; age 29.8 \u0026plusmn; 8.2; age range 18-54) from Russia. Russians, Belarusians and Ukrainians belong to the East Slavic group of Eastern Europeans. This cohort was previously described in detail (Hall et al. 2021), and a portion of that cohort had agreed to answer questions about foreign language proficiency.\u003c/p\u003e\n\u003ch2\u003ePsychometric Methods\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eTo determine engagement with foreign languages and foreign language proficiency, participants (in conjunction with their parents where appropriate) were asked to respond to questions regarding (a) what second languages they spoke (open-ended), (b) their level of immersion in foreign languages (for children only: linguistic school, non-linguistic school with extra foreign language courses, and non-linguistic school without additional foreign language courses; coded as 3,2,1, respectively), and (c) their self-reported level of foreign language proficiency (rated as beginner, elementary, intermediate, or advanced\u0026mdash;coded as 1, 2, 3, or 4, respectively).\u0026nbsp;For most participants, their second (foreign) language was English (128 children and 124 adults); for four participants their second language was German; and for one participant, their second language was French.\u003c/p\u003e\n\u003cp\u003eIntelligence was measured in children only using the Wechsler test, which includes 11 separate component sub-tests across six verbal and five non-verbal aspects. The study used two versions of the Wechsler test for two age categories of participants:\u003c/p\u003e\n\u003cp\u003e(a) 7-15 years old: Wechsler Intelligence Scale for Children (WISC) test\u0026mdash;for testing children and adolescents (Wechsler 1949). The children\u0026apos;s version of this test was adapted and standardized for Russian speakers by A. Yu. Panasyuk (Panasyk 1973).\u003c/p\u003e\n\u003cp\u003e(b) 16-21 years old: Wechsler Adult Intelligence Scale (WAIS) test\u0026mdash;designed to test adults (Wechsler 1955). This version was adapted and standardized for Russian speakers by A. Yu. Panasyuk, and supplemented and corrected by Yu. I. Filimonenko and V. I. Timofeev at the State Enterprise \u0026quot;Imaton\u0026quot;, St. Petersburg (Panasyk 1992).\u003c/p\u003e\n\u003cp\u003eBoth intelligence test versions were translated into the Kazakh language for those children for whom the Kazakh language was their first language. Cronbach\u0026rsquo;s alpha internal consistency reliability for the intelligence tests within the present samples are shown in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eCronbach\u0026apos;s alpha for the Kazakh and Russian versions of Wechsler Intelligence Scales\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTests\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLanguage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCronbach\u0026apos;s alpha\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cem\u003eWechsler Intelligence Scale for Children\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eGeneral\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eKazakh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eRussian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eVerbal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eKazakh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eRussian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNonverbal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eKazakh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eRussian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cem\u003eWechsler Adult Intelligence Scale\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eGeneral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eKazakh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eRussian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eVerbal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eKazakh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eRussian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNonverbal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eKazakh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eRussian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cbr\u003e\n\u003ch2\u003eGenetic Analysis\u003c/h2\u003e\n\u003cp\u003eIn this study, seven key genetic markers that are connected with memory capacity were selected and genotyped in the studied samples (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u003c/strong\u003e \u003cstrong\u003e2.\u0026nbsp;\u003c/strong\u003eList of selected genetic markers associated with memory\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"678\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePolymorphism\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlleles\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFavorable allele\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cem\u003eCAMTA1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ers4908449\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eT/C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003eHuentelman et al., 2007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cem\u003eCLSTN2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ers6439886\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eA/G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003ePapassotiropoulos et al., 2006; Preuschhof et al., 2010; Laukka et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cem\u003eCOMT\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ers4680\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eG/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003eAguilera et al., 2008; Miskowiak et al., 2017; Sugiura et al., 2017; Dumontheil et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cem\u003eCPEB3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ers11186856\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eA/G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003eVogler et al., 2009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cem\u003eSCN1A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ers10930201\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eA/C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003ePapassotiropoulos et al., 2011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cem\u003eSNAP25\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ers3746544\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eG/T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003eWang et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cem\u003eWWC1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ers17070145\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eC/T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003ePapassotiropoulos et al., 2006; Preuschhof et al., 2009; Milnik et al., 2012; Zlomuzica et al., 2018; Stickel\u0026nbsp;et al., 2018; Laukka et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cbr\u003e\n\u003cp\u003eGenetic markers were selected based on reproducibility of results, sample size of each study, and methodology (some markers were discovered in the genome-wide association studies, such as \u003cem\u003eCLSTN2\u003c/em\u003e rs6439886, \u003cem\u003eSCN1A\u003c/em\u003e rs10930201, and \u003cem\u003eWWC1\u003c/em\u003e rs17070145).\u003c/p\u003e\n\u003ch3\u003eGenotyping of children\u0026rsquo;s DNA samples\u003c/h3\u003e\n\u003cp\u003eSamples were collected using a non-invasive method of sampling the epithelium of cells from the oral cavity of the 129 participants. DNA was extracted from the buccal swab samples using a QIAamp DNA Mini kit (Cat No. 51306; Qiagen, Germany) according to the manufacturer\u0026rsquo;s instructions. Samples were processed as previously described (Ahmetov et al. 2023). Genomic DNA quantity and quality were assessed using a Nanodrop2000 spectrophotometer (Thermo Scientific, Massachusetts, USA). \u003cem\u003eIn silico\u003c/em\u003e primers design was performed to cover the seven selected SNPs. The primer sequences used for genotyping are listed in Table 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eList of primers used for the targeted next-generation sequencing\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"101%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoly-morphism\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eForward Primer Sequence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReverse Primer Sequence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cem\u003eCAMTA1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ers4908449\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003eTTATTGGCCTATCTCCTTGCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eGAGAAAGATGGGCGGAGAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cem\u003eCLSTN2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ers6439886\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003eGGAAGAGGGGCAGAGATTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eTGAAACTGACAGTCGGCACA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cem\u003eCOMT\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ers4680\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003eGAGATCAACCCCGACTGTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eCTGGTGGGGAGGACAAAGT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cem\u003eCPEB3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ers11186856\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003eTGCTGTTTGACTTGGGTGGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eCTAAATTCAAGGATCAAGGGG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cem\u003eSCN1A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ers10930201\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003eTGTTATCTACTTTCTGTTACTTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eCTTCTCTTGGCTAATTGTCTTA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cem\u003eSNAP25\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ers3746544\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003eACACACATCAGTCCACCCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eAACAGCACATTGAGCATTCCT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cem\u003eWWC1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ers17070145\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003eTACTCCCAGCACACACCTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eGTTGGCAGATGGAACCCGT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cbr\u003e\n\u003cp\u003eFirst, the primers were evaluated using control DNA samples, and the expected PCR product size was validated using agarose gel electrophoresis. Next, the primers were tagged with Fluidigm-specific tag sequences CS1: ACACTGACGACATGGTTCTACA for the forward\u0026rsquo;s primer, and CS2: TACGGTAGCAGAGACTTGGTCT for the reverse\u0026rsquo;s primer. The libraries for DNA sequencing using the Fluidigm Access Array microfluidic chip were generated as previously described (Gouda et al. 2022). Samples were pooled and sequenced using the Ion 520\u0026trade; Chip on the Ion S5 XL Semiconductor sequencer following the manufacturer\u0026rsquo;s instructions (Thermo Fischer). The genomic data were treated using an in-house bioinformatics pipeline, including alignment to the reference genome GRCh37/hg19, quality control assessment, SNP calling, and variant annotation as previously described (Jalaleddine et al. 2022). SNP genotyping of the seven studied markers was collected for all samples. The Functional annotation of the variants was performed using the Ensembl Variant Effect Predictor tool (McLaren et al. 2016).\u003c/p\u003e\n\u003ch3\u003eGenotyping of adults\u0026rsquo; DNA samples\u003c/h3\u003e\n\u003cp\u003eMolecular genetic analysis was performed with DNA samples obtained from leukocytes (venous blood). Four ml of venous blood were collected in tubes containing EDTA (Vacuette EDTA tubes, Greiner Bio-One, Kremsm\u0026uuml;nster, Austria). DNA extraction and purification were performed using a commercial kit according to the manufacturer\u0026rsquo;s instructions (Technoclon, Moscow, Russia). HumanOmniExpressBeadChips (Illumina Inc., San Diego, CA, USA) were used to genotype seven polymorphisms, as previously described (Boulygina et al. 2020).\u003c/p\u003e\n\u003ch2\u003eStatistical Analyses\u003c/h2\u003e\n\u003cp\u003eStatistical analyses were conducted using GraphPad InStat (GraphPad Software, Inc., San Diego, CA, USA) software. Multiple regression analyses were used to assess the relationships between self-reported foreign language proficiency and genetically predicted memory capacity (number of favourable alleles from 0 to 14) and all other variables (sex, age, ethnicity, verbal IQ, and level of immersion in foreign languages for children; sex, age, and ethnicity, for adults), and to determine the combined association (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026mdash;the percentage of variance in self-reported foreign language proficiency) of individual factors adjusted for covariates. All data are presented as mean (SD).\u0026nbsp;\u003cem\u003eP\u003c/em\u003e values \u0026lt; 0.05 were considered statistically significant.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe genotype distribution and allelic frequencies of the seven SNPs linked to memory function in the two cohorts are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The number of memory-increasing (favourable) alleles (minimum \u0026ndash; 0, maximum \u0026ndash; 14) ranged from 2 to 10 for children, and from 2 to 11 for adults.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGenotype and allele frequencies of 7 memory-related SNPs in children (n\u0026thinsp;=\u0026thinsp;129) and adults (n\u0026thinsp;=\u0026thinsp;128).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolymorphism\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenotype 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGenotype 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGenotype 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMemory-increasing allele frequency, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChildren\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCAMTA1\u003c/em\u003e rs4908449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTT (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTC (49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCC (60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT (34.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCLSTN2\u003c/em\u003e rs6439886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGG (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAG (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAA (110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eG (7.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCOMT\u003c/em\u003e rs4680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAA (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGA (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGG (92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eA (21.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCPEB3\u003c/em\u003e rs11186856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAA (107)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAG (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGG (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eA (90.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSCN1A\u003c/em\u003e rs10930201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAA (39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAC (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCC (89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eA (30.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSNAP25\u003c/em\u003e rs3746544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGG (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGT (67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTT (51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eG (34.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eWWC1\u003c/em\u003e rs17070145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTT (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCT (67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCC (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT (58.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdults\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCAMTA1\u003c/em\u003e rs4908449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTT (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTC (46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCC (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT (37.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCLSTN2\u003c/em\u003e rs6439886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGG (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAG (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAA (96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eG (13.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCOMT\u003c/em\u003e rs4680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAA (32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGA (70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGG (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eA (52.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCPEB3\u003c/em\u003e rs11186856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAA (69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAG (49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGG (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eA (73.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSCN1A\u003c/em\u003e rs10930201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAA (56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAC (62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCC (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eA (68.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSNAP25\u003c/em\u003e rs3746544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGG (17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGT (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTT (54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eG (35.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eWWC1\u003c/em\u003e rs17070145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTT (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCT (59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCC (49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT (38.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSex had no significant effect on any of the tested variables of the children, including verbal IQ (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.402), self-reported foreign language proficiency (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.486), level of immersion in foreign languages (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.756) and number of memory-increasing alleles (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.312). Furthermore, there were no significant differences in the number of memory-increasing alleles between Kazakhs and Russians living in Kazakhstan. We therefore felt justified to combine all participants into one group for further analyses. In children, we found that genetically predicted memory capacity (number of memory-increasing alleles) was positively associated with self-reported foreign language proficiency (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.108, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0048, adjusted for age, sex, ethnicity, verbal IQ, and level of immersion in foreign languages). Furthermore, age (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), level of immersion in foreign languages (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.3; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0026) and verbal IQ (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0006) were also positively associated with children\u0026rsquo;s self-reported foreign language proficiency. When combined, genetically predicted memory capacity, age, sex, ethnicity, verbal IQ, and level of immersion in foreign languages explained 32% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) of the variance in children\u0026rsquo;s self-reported foreign language proficiency.\u003c/p\u003e \u003cp\u003eIn adults, age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.180), sex (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.149), and ethnicity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.799) had no effect on self-reported foreign language proficiency. Furthermore, there were no significant differences in the number of memory-increasing alleles between Russians and the other two East Slavic ethnic groups (Belarusians and Ukrainians). We therefore felt justified to combine all participants into one group for further analyses. The positive association between genetically predicted memory capacity and self-reported foreign language proficiency was replicated in adults (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0158 adjusted for age, sex and ethnicity).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our knowledge, this is the first study to show that genetically determined memory capacity is positively associated with self-reported foreign language proficiency. Alongside this key finding, we demonstrated that age, level of immersion in foreign languages, and verbal IQ were also positively associated with self-reported foreign language proficiency. Of particular note, we were able to replicate our findings in children with a separate sample of adults.\u003c/p\u003e \u003cp\u003eOur study was based on a body of past research showing that multiple cognitive skills, including working memory, are important for effective language learning (Mechelli et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Seven genetic variants used in our research have previously been linked to memory and other cognitive-related traits, such as spatial ability, intelligence and educational attainment. These variants are located in genes (\u003cem\u003eCAMTA1\u003c/em\u003e, \u003cem\u003eCLSTN2\u003c/em\u003e, \u003cem\u003eCOMT\u003c/em\u003e, \u003cem\u003eCPEB3\u003c/em\u003e, \u003cem\u003eSCN1A\u003c/em\u003e, \u003cem\u003eSNAP25\u003c/em\u003e, and \u003cem\u003eWWC1\u003c/em\u003e) responsible for neurological processes that underlie memory and cognitive function, including synaptic plasticity, neurogenesis, and neurotransmission.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eCAMTA1\u003c/em\u003e gene encodes calmodulin-binding transcription activator 1, which interfaces with the calcium-calmodulin system of the cell to alter gene expression patterns (Huentelman et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Carriers of the \u003cem\u003eCAMTA1\u003c/em\u003e rs4908449 T allele have been shown to demonstrate better performance in an episodic recall memory test (Huentelman et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The \u003cem\u003eCLSTN2\u003c/em\u003e gene encodes calsyntenin 2, and is involved in positive regulation of synapse assembly and positive regulation of synaptic transmission (Preuschhof et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Carriers of the \u003cem\u003eCLSTN2\u003c/em\u003e rs6439886 G allele have better episodic memory (Preuschhof et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Papassotiropoulos et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Laukka et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The \u003cem\u003eCOMT\u003c/em\u003e gene encodes catechol-O-methyltransferase, which catalyzes the transfer of a methyl group from S-adenosylmethionine to catecholamines, including the neurotransmitters dopamine, epinephrine, and norepinephrine. The \u003cem\u003eCOMT\u003c/em\u003e rs4680 A allele has been reported to be associated with better verbal working memory (Aguilera et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), language ability (Sugiura et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), spatial working memory (Miskowiak et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and visuospatial and social working memory (Dumontheil et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The \u003cem\u003eCPEB3\u003c/em\u003e gene encodes cytoplasmic polyadenylation element binding protein 3, which is crucial for synaptic plasticity and memory in model organisms (Dumontheil et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The \u003cem\u003eCPEB3\u003c/em\u003e rs11186856 A allele is associated with episodic memory (Vogler et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The \u003cem\u003eSCN1A\u003c/em\u003e gene encodes sodium voltage-gated channel alpha subunit 1 and regulates the release of neurotransmitters in neurons. The \u003cem\u003eSCN1A\u003c/em\u003e rs10930201 A allele has been linked with short-term memory (Papassotiropoulos et al. 2011). The \u003cem\u003eSNAP25\u003c/em\u003e gene encodes synaptosome associated protein 25, which plays an important role in the synaptic function of specific neuronal systems. The \u003cem\u003eSNAP25\u003c/em\u003e rs3746544 G allele has been reported to be associated with better brain functional connectivity density and working memory (Wang et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The \u003cem\u003eWWC1\u003c/em\u003e (also known as \u003cem\u003eKIBRA\u003c/em\u003e) gene encodes WW and C2 domain containing 1 protein, which together with its binding partners (dendrin, synaptopodin, dynein-complex, and others) plays an important role in synaptic plasticity (18). The \u003cem\u003eWWC1\u003c/em\u003e gene rs17070145 T allele has been linked with better episodic and working memory (Ahmetov et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Preuschhof et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Milnik et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zlomuzica et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Laukka et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and verbal memory (Stickel et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAgainst the backdrop of this study\u0026rsquo;s novel findings, there are some limitations that should be acknowledged. First, our cohort of children was heterogeneous with respect to age, ethnicity and level of immersion in foreign languages. We therefore adjusted our findings for these and other (sex and verbal IQ) covariates. Second, to test foreign language proficiency, we used a self-reported phenotype (a survey question), which was swift to administer, but we acknowledge the availability of various objective assessments of foreign language proficiency (e.g., TOEFL, IELTS, etc.). Finally, our study is limited to the seven common polymorphisms which were primarily selected because of previously reported associations with memory capacity. It is likely, however, that future research will show that many additional common polymorphisms, and probably rare mutations as well, are associated with memory capacity and foreign language proficiency.\u003c/p\u003e \u003cp\u003eOverall, our research provides strong support for the idea that memory function and linguistic abilities are genetically linked. Indeed, the present study suggests that self-reported foreign language proficiency may partly depend on the presence of a high number of memory-increasing alleles in both children and adults. The process behind genetically predicted memory capacity and self-reported foreign language proficiency needs to be further investigated in order to develop individualized teaching methods and interventions targeted at enhancing language learning results. This study also highlights that researchers examining cognitive variables and educational policy-makers would be well-advised to consider taking into account the influence of genetic variables, especially with regard to memory and language development.\u003c/p\u003e"},{"header":"Declarations","content":" \u003ch2\u003eConflict of Interest\u003c/h2\u003e \u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe Kazakhstan part of the study was funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. BR27198099).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMBY: formal analysis, investigation, writing \u0026ndash; original draft; GKD: formal analysis, investigation; MKZ: investigation; ATK: investigation; ZMS: investigation; AB: investigation; PMB: investigation; RH: investigation; EAS: formal analysis; AKL: investigation; NAK: formal analysis; EVG: investigation, resources, project administration; TR: formal analysis, writing \u0026ndash; review \u0026amp; editing; AMK: conceptualization, supervision, funding acquisition, methodology, resources, project administration (PI), writing \u0026ndash; review \u0026amp; editing; IIA: conceptualization, formal analysis, methodology, writing \u0026ndash; original draft. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAguilera M, Barrantes-Vidal N, Arias B, Moya J, Villa H, Ib\u0026aacute;\u0026ntilde;ez MI, Ruip\u0026eacute;rez MA, Ortet G, Fa\u0026ntilde;an\u0026aacute;s L (2008) Putative role of the COMT gene polymorphism (Val158Met) on verbal working memory functioning in a healthy population. Am J Med Genet B Neuropsychiatr Genet 147B:898\u0026ndash;902. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ajmg.b.30705\u003c/span\u003e\u003cspan address=\"10.1002/ajmg.b.30705\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmetov II, Valeeva EV, Yerdenova MB, Datkhabayeva GK, Bouzid A, Bhamidimarri PM, Sharafetdinova LM, Egorova ES, Semenova EA, Gabdrakhmanova LJ, Yusupov RA, Larin AK, Kulemin NA, Generozov EV, Hamoudi R, Kustubayeva AM, Rees T (2023) KIBRA gene variant is associated with ability in chess and science. Genes 14:204. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/genes14010204\u003c/span\u003e\u003cspan address=\"10.3390/genes14010204\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoulygina EA, Borisov OV, Valeeva EV, Semenova EA, Kostryukova ES, Kulemin NA, Larin AK, Nabiullina RM, Mavliev FA, Akhatov AM, Andryushchenko ON, Andryushchenko LB, Zmijewski P, Generozov EV, Ahmetov II (2020) Whole genome sequencing of elite athletes. Biol Sport 37(3):295\u0026ndash;304. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5114/biolsport.2020.96272\u003c/span\u003e\u003cspan address=\"10.5114/biolsport.2020.96272\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Moor SAG, De Kort MHM, Boomsma DI (2018) Biochemical genetics of human memory. Psychon Bull Rev 25:187\u0026ndash;202\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDumontheil I, Kilford EJ, Blakemore SJ (2020) Development of dopaminergic genetic associations with visuospatial, verbal and social working memory. Dev Sci 23(2):e12889. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/desc.12889\u003c/span\u003e\u003cspan address=\"10.1111/desc.12889\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGouda HR, Talaat IM, Bouzid A, El-Assi H, Nabil A, Venkatachalam T, Manasa Bhamidimarri P, Wohlers I, Mahdami A, El-Gendi S, ElKoraie A, Busch H, Saber-Ayad M, Hamoudi R, Baddour N (2022) Genetic analysis of CFH and MCP in Egyptian patients with immune-complex proliferative glomerulonephritis. Front Immunol 13:960068. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fimmu.2022.960068\u003c/span\u003e\u003cspan address=\"10.3389/fimmu.2022.960068\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHall ECR, Semenova EA, Bondareva EA, Borisov OV, Andryushchenko ON, Andryushchenko LB, Zmijewski P, Generozov EV, Ahmetov II (2021) Association of muscle fiber composition with health and exercise-related traits in athletes and untrained subjects. Biol Sport 38:659\u0026ndash;666. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5114/biolsport.2021.102923\u003c/span\u003e\u003cspan address=\"10.5114/biolsport.2021.102923\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoward HC, Borry P (2012) Is there a doctor in the house? The presence of physicians in the direct-to-consumer genetic testing context. J Community Genet 3(2):105\u0026ndash;112. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12687-011-0062-0\u003c/span\u003e\u003cspan address=\"10.1007/s12687-011-0062-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuentelman MJ, Papassotiropoulos A, Craig DW, Hoerndli FJ, Pearson JV, Huynh KD, Corneveaux J, H\u0026auml;nggi J, Mondadori CR, Buchmann A, Reiman EM, Henke K, de Quervain DJ, Stephan DA (2007) Calmodulin-binding transcription activator 1 (CAMTA1) alleles predispose human episodic memory performance. Hum Mol Genet 16(12):1469\u0026ndash;1477. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/hmg/ddm097\u003c/span\u003e\u003cspan address=\"10.1093/hmg/ddm097\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJalaleddine N, Bouzid A, Hachim M, Sharif-Askari NS, Mahboub B, Senok A, Halwani R, Hamoudi RA, Al Heialy S (2022) ACE2 polymorphisms impact COVID-19 severity in obese patients. Sci Rep 12(1):21491. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-022-26072-7\u003c/span\u003e\u003cspan address=\"10.1038/s41598-022-26072-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKere J (2014) The molecular genetics and neurobiology of developmental dyslexia as model of a complex phenotype. Biochem Biophys Res Commun 452(2):236\u0026ndash;243. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.bbrc.2014.07.102\u003c/span\u003e\u003cspan address=\"10.1016/j.bbrc.2014.07.102\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaukka EJ, K\u0026ouml;hncke Y, Papenberg G, Fratiglioni L, B\u0026auml;ckman L (2020) Combined genetic influences on episodic memory decline in older adults without dementia. Neuropsychology 34(6):654\u0026ndash;666. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/neu0000637\u003c/span\u003e\u003cspan address=\"10.1037/neu0000637\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, Flicek P, Cunningham F (2016) The Ensembl Variant Effect Predictor. Genome Biol 17(1):122. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13059-016-0974-4\u003c/span\u003e\u003cspan address=\"10.1186/s13059-016-0974-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMechelli A, Price CJ, Friston KJ, Ashburner R (2005) Voxel-based morphometry of the human brain: Methods and applications. Curr Med Imag Rev 1:105\u0026ndash;113\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMilnik A, Heck A, Vogler C, Heinze HJ, de Quervain DJ, Papassotiropoulos A (2012) Association of KIBRA with episodic and working memory: A meta-analysis. Am J Med Genet B Neuropsychiatr Genet 159(8):58\u0026ndash;69. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ajmg.b.32101\u003c/span\u003e\u003cspan address=\"10.1002/ajmg.b.32101\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiskowiak KW, Kjaerstad HL, St\u0026oslash;ttrup MM, Svendsen AM, Demant KM, Hoeffding LK, Werge TM, Burdick KE, Domschke K, Carvalho AF, Vieta E, Vinberg M, Kessing LV, Siebner HR, Macoveanu J (2017) The catechol-O-methyltransferase (COMT) Val158Met genotype modulates working memory-related dorsolateral prefrontal response and performance in bipolar disorder. Bipolar Disord 19(3):214\u0026ndash;224. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/bdi.12497\u003c/span\u003e\u003cspan address=\"10.1111/bdi.12497\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePanasyk A (1973) Adaptirovannyi variant metodiki D. Vekslera (WISC) (Adapted version of the methodology of D. Veksler (WISC)). Institute of Hygiene of Children and Adolescents of the USSR Ministry of Health\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePanasyk A, Filimonenko Y, Timofeev V (1992) Rukovodstvo k metodike issledovaniya intellekta u detei D. Veksler (Guide to the methodology of the study of intelligence in children by D. Wexler). State Enterprise IMATON\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapassotiropoulos A, de Quervain DJ (2011) Genetics of human episodic memory: Dealing with complexity. Trends Cogn Sci 15(9):381\u0026ndash;387. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tics.2011.07.005\u003c/span\u003e\u003cspan address=\"10.1016/j.tics.2011.07.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapassotiropoulos A, Stephan DA, Huentelman MJ, Hoerndli FJ, Craig DW, Pearson JV, Huynh KD, Brunner F, Corneveaux J, Osborne D, Wollmer MA, Aerni A, Coluccia D, H\u0026auml;nggi J, Mondadori CR, Buchmann A, Reiman EM, Caselli RJ, Henke K, de Quervain DJ (2006) Common Kibra alleles are associated with human memory performance. Science 314(5798):475\u0026ndash;478. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1126/science.1129837\u003c/span\u003e\u003cspan address=\"10.1126/science.1129837\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePayton ES (2009) The impact of genetic research on our understanding of normal cognitive ageing: 1995 to 2009. Neuropsychol Rev 19:451\u0026ndash;477. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11065-009-9116-z\u003c/span\u003e\u003cspan address=\"10.1007/s11065-009-9116-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePennington BF (2006) From single to multiple deficit models of developmental disorders. Cognition 101(2):385\u0026ndash;413. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cognition.2006.04.008\u003c/span\u003e\u003cspan address=\"10.1016/j.cognition.2006.04.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePlomin R, Spinath FM (2004) Intelligence: Genetics, genes, and genomics. J Pers Soc Psychol 86(1):112\u0026ndash;129. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0022-3514.86.1.112\u003c/span\u003e\u003cspan address=\"10.1037/0022-3514.86.1.112\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePlomin R, Von Stumm S (2018) The new genetics of intelligence. Nat Rev Genet 19:148\u0026ndash;159. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nrg.2017.104\u003c/span\u003e\u003cspan address=\"10.1038/nrg.2017.104\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePosthuma D, Boomsma DI (2000) A note on the statistical power in extended twin designs. Behav Genet 30(2):147\u0026ndash;158. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1023/a:1001959306025\u003c/span\u003e\u003cspan address=\"10.1023/a:1001959306025\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePreuschhof C, Heekeren HR, Li SC, Sander T, Lindenberger U, B\u0026auml;ckman L (2010) KIBRA and CLSTN2 polymorphisms exert interactive effects on human episodic memory. Neuropsychologia 48(2):402\u0026ndash;408. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuropsychologia.2009.09.031\u003c/span\u003e\u003cspan address=\"10.1016/j.neuropsychologia.2009.09.031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStickel A, Kawa K, Walther K, Glisky E, Richholt R, Huentelman M, Ryan L (2018) Age-modulated associations between KIBRA, brain volume, and verbal memory among healthy older adults. Front Aging Neurosci 10:431. https://doi.org/10.3389\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSugiura L, Toyota T, Matsuba-Kurita H, Iwayama Y, Mazuka R, Yoshikawa T, Hagiwara H (2017) Age-dependent effects of catechol-O-methyltransferase (COMT) gene Val158Met polymorphism on language function in developing children. Cereb Cortex 27(1):104\u0026ndash;116. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/cercor/bhw371\u003c/span\u003e\u003cspan address=\"10.1093/cercor/bhw371\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThompson C (2018) The role of practice within second language acquisition. In: Jones C (ed) Practice in second language learning. Cambridge University Press, pp 30\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/9781316443118.004\u003c/span\u003e\u003cspan address=\"10.1017/9781316443118.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVisscher PM, Wray NR, Zhang Q, Sklar P, McCarthy MI, Brown MA, Yang J (2017) 10 years of GWAS discovery: Biology, function, and translation. Am J Hum Genet 101(1):5\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ajhg.2017.06.005\u003c/span\u003e\u003cspan address=\"10.1016/j.ajhg.2017.06.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVogler C, Spalek K, Aerni A, Demougin P, M\u0026uuml;ller A, Huynh KD, Papassotiropoulos A, de Quervain DJ (2009) CPEB3 is associated with human episodic memory. Front Behav Neurosci 3:4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/neuro.08.004.2009\u003c/span\u003e\u003cspan address=\"10.3389/neuro.08.004.2009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang C, Yang B, Fang D, Zeng H, Chen X, Peng G, Cheng Q, Liang G (2018) The impact of SNAP25 on brain functional connectivity density and working memory in ADHD. Biol Psychol 138:35\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.biopsycho.2018.08.005\u003c/span\u003e\u003cspan address=\"10.1016/j.biopsycho.2018.08.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWechsler D (1949) Wechsler intelligence scale for children. The Psychological Corporation\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWechsler D (1955) Manual for the Wechsler Adult Intelligence Scale. The Psychological Corporation\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZlomuzica A, Preusser F, Roberts S, Woud ML, Lester KJ, Dere E, Eley TC, Margraf J (2018) The role of KIBRA in reconstructive episodic memory. Mol Med 24(1):7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s10020-018-0007-8\u003c/span\u003e\u003cspan address=\"10.1186/s10020-018-0007-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Genetic markers, Intelligence, Linguistic immersion, Language abilities, Cognitive development, Behaviour genetics, Cognitive abilities","lastPublishedDoi":"10.21203/rs.3.rs-5601729/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5601729/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlthough contextual variables have a considerable impact on linguistic ability, the effect of genetic factors, especially those linked to memory function, remains poorly understood. The aim of this study was to establish the relationship between genetically determined memory capacity and self-reported foreign language proficiency in 129 children (63 males, 66 females, age 14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9) and 128 adults (90 males, 38 females, age 29.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2). Seven single nucleotide polymorphisms (SNPs) previously linked with memory function were used in a polygenic analysis (\u003cem\u003eCAMTA1\u003c/em\u003e rs4908449, \u003cem\u003eCLSTN2\u003c/em\u003e rs6439886, \u003cem\u003eCOMT\u003c/em\u003e rs4680, \u003cem\u003eCPEB3\u003c/em\u003e rs11186856, \u003cem\u003eSCN1A\u003c/em\u003e rs10930201, \u003cem\u003eSNAP25\u003c/em\u003e rs3746544, and \u003cem\u003eWWC1\u003c/em\u003e rs17070145). Self-reported foreign language proficiency was evaluated using a single-item question. Children's level of immersion in foreign languages was divided into three categories: linguistic school, non-linguistic school with extra foreign language courses, and non-linguistic school without additional foreign language courses. We found that genetically predicted memory capacity (i.e., number of memory-increasing alleles) was positively associated with self-reported foreign language proficiency in children (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0078) adjusted for age, sex, ethnicity, verbal IQ, and level of immersion in foreign languages. Further, age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), level of immersion in foreign languages (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0035) and verbal IQ (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0004) were also positively associated with self-reported foreign language proficiency in children. The association between genetically predicted memory capacity and self-reported foreign language proficiency was replicated in adults (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0158 adjusted for age, sex and ethnicity). In conclusion, foreign language proficiency may partly depend on the presence of a high number of memory-increasing alleles in both children and adults.\u003c/p\u003e","manuscriptTitle":"Association Between Genetically Predicted Memory and Self-Reported Foreign Language Proficiency","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-18 04:31:55","doi":"10.21203/rs.3.rs-5601729/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"950dfff9-89a9-467b-91ff-8ea61d84d1ba","owner":[],"postedDate":"March 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-18T04:31:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-18 04:31:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5601729","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5601729","identity":"rs-5601729","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}