Association of Stmn1 Polymorphism and Cognitive Function: An Observational Study in the Chinese Adults

Abstract

Background:

Stathmin1 (Stmn1) is a protein highly expressed during the development of the central nervous system. The phosphorylation of Stmn1 involves microtubule dynamics, so Stmn1 plays a vital part in neurite outgrowth and synaptic plasticity. Previous studies reported that Stmn1 genetic variants influence fear and anxiety as well as cognitive-affective processing. However, no study reported on the relationship between Stmn1 gene polymorphism and cognition in Chinese. Thus, this association was investigated in the present study.

Methods:

A total of 129 healthy Han Chinese were genotyped for Stmn1 rs182455 polymorphism by polymerase chain reaction and restriction fragment length polymorphism analyses. Cognitive function was assessed using the Stroop Color-Word Test (SCWT) and Hopkins Verbal Learning Test-Revised (HVLT-R).

Results:

In the present sample, rs182455 CC, CT, and TT genotypes were found in 56 (43.41%), 65 (50.39%) and 8 (6.20%) cases, respectively. The genotype distribution did not deviate from Hardy-Weinberg equilibrium (χ² = 3.715, p = 0.054). Significant differences were found between the three rs182455 genotypes and between the CC and (CT+TT) genotype groups in the Stroop Color (SC) scores of the SCWT (F = 3.322, 2.377; p = 0.039, 0.019, respectively) and the total recall (TR) scores on the HVLT-R (F = 3.118, 2.225; p = 0.048, 0.028, respectively). There was a female-specific difference in SC scores between the three rs182455 genotypes (F = 2.318, p = 0.023). The rs182455 genotype distribution showed no significant difference between two sexes (χ² = 1.313, p = 0.519), whereas significant differences were seen in SC and TR scores between two sexes (t = –2.294, –2.490; p = 0.023, 0.014, respectively).

Conclusions:

The findings suggest that rs182455 Stmn1 polymorphism might affect cognitive flexibility and immediate free recall in healthy Chinese individuals, especially females.

Keywords

Stmn1 / gene polymorphism / cognitive function / Stroop Color-Word Test / Hopkins Verbal Learning Test

Main Points

1. The number of CC, CT, and TT rs182455 polymorphism genotypes was 56 (43.41%), 65 (50.39%) and 8 (6.20%), respectively, which did not deviate from Hardy-Weinberg equilibrium.

2. Significant differences were found between the three rs182455 genotypes and the CC and (CT+TT) genotype groups in Stroop Color (SC) scores on the Stroop Color-Word Test (SCWT) and total recall (TR) scores on the Hopkins Verbal Learning Test-Revised (HVLT-R).

3. Female-specific differences in SC scores were found between the three rs182455 genotypes.

1. Introduction

The human brain receives input from the outside world and converts it to internal psychological activity to control individual behaviors; this is the cognitive process [1]. Cognition, which is the most basic human psychological process, refers to acquiring knowledge, applying knowledge, or processing information. Cognition is critical to normal psychological function and cognitive impairment is the core symptom of many disorders, including neurodegenerative (e.g., Alzheimer’s disease (AD)) [2, 3, 4] and psychiatric diseases (e.g., schizophrenia and affective disorders) [4, 5]. Therefore, it is important to investigate the factors that contribute to cognition.

Intelligence is a general cognitive ability and a quantitative trait that accounts for much of the variation in diverse cognitive abilities. Previous studies demonstrated that general cognitive ability is approximately 50%–70% heritable [6, 7], meaning that genetic differences account for more than 50% of individual variation in performance on tests of cognitive ability. In contrast, the influence of the environment on general cognitive ability is less significant and unstable [8]. Twin studies and molecular genetic studies of unrelated persons have both converged on similar heritability estimates [9, 10]. Cognitive functions other than intelligence include diverse abilities, such as reasoning, memory, selective attention, processing speed, mental rotation, knowledge, and executive function. However, less research has been conducted on factors related to cognitive functions beyond intelligence.

In recent decades, the assessment of cognitive functions has gained increasing widespread attention. Previous studies focused on the effect of Stathmin1 (Stmn1) polymorphisms on individual emotion regulation, whereas the present study planned to evaluate an individual’s ability to inhibit a habitual response and react selectively to information, as well as complicated verbal learning and memory, which is different from and more multifaceted than previous studies. The Stroop Color-Word Test (SCWT) is a frequently used test that measures an individual’s ability to inhibit the normal response in favor of an unexpected response [11]. Previous studies have revealed the functions of the SCWT to assess cognitive abilities including selective attention, processing speed, working memory, and cognitive flexibility [12, 13]. In the present study, the SCWT was used to evaluate the participants’ ability to inhibit a habitual response and react selectively to information. The Hopkins Verbal Learning Test-Revised (HVLT-R) is a multicomponent wordlist learning task developed to assess verbal learning and memory [14], which are important aspects of cognitive function. The utility and validity of the HVLT-R have been demonstrated in individuals with a wide range of different races and ethnicities with significant cognitive impairments, such as AD [15, 16, 17] and Huntington’s disease [18]. It also has high ability of classification accuracy for distinguishing individuals with dementia from those without dementia [15, 19] and patients with AD from those with vascular dementia [17, 20]. Therefore, the HVLT-R was used to evaluate verbal learning and memory function for the participants in the present study.

Stmn1 is highly expressed in central nervous system brain regions, such as the amygdala, prefrontal cortex, and nucleus accumbens, in both mice and humans [4, 21, 22]. It is involved in microtubule (MT) dynamics and neuronal growth and, thus, plays a vital part in neurite outgrowth and synaptic plasticity [23]. Synaptic plasticity refers to the property that the connection strength and functional properties of synapses can change. This plasticity is the basis for the ability of the nervous system to adapt to environmental changes and to execute cognitive functions such as learning and memory. Synaptic plasticity mainly includes short-term and long-term types. Long-term potentiation (LTP) is an important manifestation of long-term synaptic plasticity, which refers to the phenomenon of persistent enhancement of synaptic transmission efficiency and strength that occurs when synapses between two neurons are subjected to a certain form of stimulation. Currently, memory is thought to be encoded by changes in synaptic strength. Thus, LTP plays a crucial role in the process of learning to remember. However, the biological mechanism of LTP has not been fully elucidated. Animal studies found that Stmn1 gene knockout mice showed deficits in spike-timing-dependent LTP, and exhibited deficient memory related to fear conditioning and the recognition of danger in innately aversive environments, relative to wildtype controls [21].

Based on the involvement of Stmn1 in LTP and memory, it was hypothesized that Stmn1 variation primarily impacts human cognition. Brocke et al. [24] demonstrated the significant impact of two single nucleotide polymorphisms (SNPs) of the Stmn1 gene (rs182455 and rs213641) on fear and anxiety responses in healthy German volunteers. Ehlis et al. [23] demonstrated the effect of the rs182455 SNP on cognitive-affective processing in healthy German volunteers. Previous research results on the effect of Stmn1 on human emotion regulation and executive function indicated that Stmn1 genes and proteins may influence human cognitive function. However, no study has reported a correlation between Stmn1 gene polymorphisms and cognitive function assessed by the SCWT or HVLT-R. SNP rs182455 is located within or close to the putative transcriptional control region and affects the Stmn1 protein expression level. Informed by the two studies above [23, 24], the present study explored the correlation of Stmn1 SNP rs182455 with cognitive function in a healthy Chinese population.

2. Materials and Methods

2.1 Participants

On the basis of the research target and type, experimental design, resource constraints, etc., we used G*Power 3.0 (Düsseldorf, North Rhine-Westphalia, Germany), a widely used statistical software [25], to calculate the present sample size in the experimental design phase (Test family: F tests. Statistical test: One-way analysis of variance (ANOVA), fixed effects, omnibus, one-way. Input Parameters: Type I error, \alpha = 0.05; Type II error, \beta = 0.20; Effect size f = 0.30. Output Parameters: Total sample size = 111). In the present study, we employed stratified random sampling methodology. Firstly, the sample was stratified on the basis of sex, resulting in the overall sample divided into two separate strata: males and females. The sub-sample size was estimated within each stratum, primarily based on the overall sample size and the proportion of males and females in the natural population. The ratio between the two sex strata was approximately 1:1. Subsequently, among the volunteers who met the enrollment criteria, random sampling was conducted within each stratum with the assistance of a random number table. Ultimately, the sub-samples drawn from both strata were combined to form the final overall sample. A total of 136 healthy volunteers were recruited from a university in China by random stratified sampling. Seven volunteers who failed to complete the neurocognitive assessment were excluded. Thus, 129 volunteers were identified for the present study. The inclusion criteria included (1) being Chinese Han, (2) being 18–30 years old, (3) having ability to complete the neurocognitive assessments, and (4) having physical and mental health. The exclusion criteria included (1) a history of neurological, psychiatric, or severe physical illness, (2) having neurological, psychiatric, or severe physical illness, (3) being younger than 18 or more than 30 years old, (4) not able to complete the neurocognitive assessment, and (5) having a relative(s) also enrolled in the present study. Each volunteer was interviewed by a psychiatrist for enrollment. Each enrolled subject provided written informed consent. The Ethics Committee of Hainan Provincial Anning Hospital approved this study (No.202206).

2.2 Neurocognitive Assessment

In 1935, Stroop [26] introduced the SCWT for the first time. Since then, the version developed by Golden & Freshwater (2002) has become the most popular [11]. In SCWT, Chinese characters are utilized as test materials, and the reaction time becomes an index to reproduce the Stroop effect because of contradictory words and colors. The SCWT consists of three pages: the first for words, the second for colors, and the last for color–words. The participants are instructed to complete the SCWT as quickly as possible during a 45-s period for each page [11]. For the first page, the participant is instructed to read the names of colors printed in black ink (W); this part is believed to represent simple reading and may be influenced by speech/motor problems or learning disabilities [27]. For the second page, the participant is asked to name the color (C) of the X symbol; this might be impaired by speech/motor function or color blindness. For the last page, each color-word is printed in a contrasting color (e.g., the word “red” is printed in blue ink), and the participant is asked to name the color of the ink, not the word, as quickly as possible. This task is assumed to measure both cognitive flexibility and the ability to inhibit the usual response [28]. The three WCST variables (subscores) are the scores of the Stroop Word (SW), Stroop Color (SC), and Stroop Color-Word (SCW) tests.

The HVLT-R developed by Benedict et al. [14] is an extension of the HVLT [29]. It consists of 12 nouns, with four words drawn from each of three semantic categories. The participant reads the list at a rate of one word per 2 s, and then attempts to freely recall as many words as they can remember in any order. Correct responses range from 0 to 12, with no deduction for repeated words. The trial involves the presentation of the word list and then free recall is repeated twice, yielding total immediate recall scores ranging from 0 to 36. The delayed recall component occurs after a delay of 20–25 min (occupied by non-verbal tasks). The participant is asked to recall the same list of words without the benefit of having them presented before the recall. The delayed recognition trial immediately follows, in which a list of 24 words is read. This list includes 12 words from the recall list and 12 false positives, half of which are semantically related to the recall list and half are not. The participant must state if each word appeared on the original list. The HVLT-R is composed of three free recall learning trials, a delayed recall trial, and a recognition task [30]. The four HVLT-R variables (subscores) are the scores of total recall (TR), delayed recall (DR), true positives (TPs), and false positives (FPs).

2.3 Genotyping

Each subject had a 2 mL venous blood drawn for genotyping. Genomic DNA was extracted by the standard potassium iodide method. Polymerase chain reaction was used to amplify gene fragments containing Stmn1 SNP rs182455, and restriction fragment length polymorphism analysis was used for subsequent genotyping, which was carried out as described in our previous studies [31, 32, 33]. The rs182455 genotype of each subject was identified independently by two different analysts. When the results of the two experimenters were inconsistent, the experiments were repeated separately until the results were consistent.

2.4 Statistical Analysis

The data are presented as the percent frequency or the mean and standard deviation (SD). The chi-squared test was used to assess genotype distribution and Hardy-Weinberg equilibrium (HWE). One-way analysis of variance (ANOVA) was used to compare the mean SCWT and HVLT-R scores between the three genotype groups. The independent sample t-test was used to compare the mean age, education years, and SCWT and HVLT-R scores between the male and female participants, and SCWT and HVLT-R scores between the two dominant model genotype groups or two recessive model genotype groups. A p-value 0.05 was set as the level of statistical significance. The statistical software, SPSS 22.0 for Windows (SPSS Inc, Chicago, IL, USA), was used to conduct all statistical analyses.

3. Results

3.1 Sample Characteristics

A total of 129 volunteers (57 males, 44.2%; 72 females, 55.8%) were identified as the experimental subjects for the present study. The ages ranged from 20 to 26 years, with a mean age \pm standard deviation (SD) of 22.98 \pm 1.57 years. The education years ranged from 14 to 22 years, with a mean \pm SD of 17.16 \pm 1.76 years. No significant differences were found in age (t = 0.576, p = 0.566) or education years (t = 1.299, p = 0.196) between the male and female participants.

3.2 HWE Results

The genotype counts and frequencies for SNP rs182455 in the total sample are presented in Table 1. The numbers of CC, CT, and TT rs182455 genotypes were 56 (43.41%), 65 (50.39%) and 8 (6.20%), respectively. The genotype distribution was not demonstrated to deviate significantly from HWE (\chi² = 3.715, p = 0.054). Moreover, the distribution was not significantly different from that of previous samples of 160 Asian individuals (T = 0.344, \chi² = 0.573, p = 0.449) and 102 East Asian individuals (T = 0.382, \chi² = 2.361, p = 0.124) (https://www.ncbi.nlm.nih.gov/snp/rs182455). Therefore, we can consider the sample in the present study to be representative of the general Chinese population.

3.3 Relationship between Stmn1 Polymorphism and Cognitive Function in the Overall Sample

The SCWT and HVLT-R scores are presented in Table 1. The three rs182455 genotype groups (CC, CT, TT) showed significant differences in SC scores on the SCWT (F = 3.322, p = 0.039) and TR scores of the HVLT-R (F = 3.118, p = 0.048) as follows: TT CT CC for SC, and CT TT CC for TR. However, no significant differences were observed for the SW or SCW scores on the SCWT or DR, TP, or FP scores on the HVLT-R among the different genotype groups (all p > 0.05).

Subsequently, we converted the three genotype groups to two recessive model groups and two dominant model groups. Significant differences were demonstrated in SC scores on the SCWT (F = 2.377, p = 0.019) and TR scores on the HVLT-R (F = 2.225, p = 0.028) between the CC and (CT+TT) genotype groups (Table 1). In contrast, no significant differences were found for any SCWT or HVLT-R scores between the (CT+CC) and TT genotype groups (Table 1, all p > 0.05).

3.4 Relationship between Stmn1 Polymorphism and Cognitive Function in Male and Female Participants

Differences in SCWT and HVLT-R scores among the rs182455 genotype groups were analyzed separately by sex. Significant female-specific differences were found in SC scores on the SCWT among those with rs182455 genotypes (Table 2, F = 2.318, p = 0.023). However, no significant male-specific differences were found in any SCWT or HVLT-R scores (Table 3, all p > 0.05).

3.5 Sex Differences in Stmn1 Genotype Distribution and Cognitive Function

The rs182455 genotype distribution did not differ between male and female participants (\chi² =1.313, p = 0.519). Significant sex differences were found for SC scores on the SCWT and TR scores on the HVLT-R (Table 4, t = –2.294, –2.490; p = 0.023, 0.014, respectively), but not for the remaining five SCWT and HVLT-R scores (Table 4, all p > 0.05).

Subsequently, we compared SCWT and HVLT-R scores between males and females with the same genotype. Significant or marginally significant sex differences were found for SC scores on the SCWT for the CC genotype and SCW scores on the SCWT for the TT genotype (Table 4, t = –2.009, –3.163; p = 0.050, 0.019, respectively), which are both consistent (SC) and different (SCW) from the results of the above comparisons of SCWT and HVLT-R scores between males and females with all genotypes. Since only five males and three females carried the TT genotype in the present study, the significance of the differences in SCW scores between males and females carrying the TT genotype could not be determined because of the small sample size.

4. Discussion

The present study investigated the association between Stmn1 gene polymorphism and cognitive function assessed by the SCWT and HVLT-R in a Chinese population for the first time. The results showed significant effects of the SNP rs182455 CC: (CT+TT) genotype on the SC score of the SCWT and TR score of the HVLT-R in the total sample, indicating that carriers of the rs182455 CC genotype have higher immediate free recall, cognitive flexibility, and ability to inhibit usual responses.

In the last decade, meta-analyses of genome-wide association studies (GWAS) have established that human general cognitive ability is highly heritable and polygenic [10, 34, 35, 36, 37, 38, 39, 40]. Prior studies focused on general cognitive ability, namely intelligence, and identified some loci, genes, and SNPs significantly associated with intelligence. Davies et al. [40] identified 148 independent loci associated with general cognitive function by GWAS and 709 genes associated with general cognitive function using gene-based analyses. Up to 4.3% of the variance in general cognitive function could be predicted by polygenic scores in independent samples [40]. However, Stmn1 was not one of the genes associated with general cognitive ability in previous studies.

Stmn1 was the first discovered member of the stathmin family of phylogenetically related MT-destabilizing phosphoproteins, which also includes superior cervical ganglia neural-specific 10 protein (SCG10; stathmin 2), SCG10-like protein (SCLIP; stathmin 3), and RB3 (stathmin 4). Among these, Stmn1 is the most abundantly expressed in the nervous system [41]. Stmn1, a 19 kDa cytosolic protein, is composed of 149 amino acids organized into four domains defined by limited proteolysis [42]. MTs are protein polymers composed of \alpha/\beta tubulin heterodimers with essential roles in cellular structure and function, including cell motility, polarity and proliferation, intracellular transport, neurite branch growth, and synaptic plasticity [4, 43, 44, 45]. Unphosphorylated or hypophosphorylated Stmn1 interacts with tubulin heterodimers to prevent the formation of MTs [46]. Stmn1 has four phosphorylation domains: Ser 16, 25, 38 and 63 [47]. Stmn1 releases tubulin after phosphorylation, so that MT can be formed. Thus, Stmin1 is involved in MT dynamics by regulating both the formation of MT and disassembly [44] and influences neural functions. Based on these functions, researchers have investigated the impact of Stmn1 on neural function in both experimental animals and humans.

LTP is an important form of synaptic plasticity [48, 49] and is regarded as a neuronal correlate of fear, learning, and memory [50, 51]. In 2005, Shumyatsky et al. [21] reported that whole-cell recordings from amygdala slices isolated from Stmn1 knockout (KO) mice showed deficits in spike-timing-dependent LTP. Moreover, Stmn1 KO mice exhibited decreased amygdala-dependent fear conditioning memory and failed to recognize the danger in innately aversive environments [21]. In 2008, Martel et al. [52] reported that Stmn1 KO mice showed an increase in social interactions but a decrease in social recognition memory and affiliative maternal care, which were associated with Stmn1 expression in the basolateral amygdala. In 2014, Uchida et al. [53] demonstrated that Stmn1 transgenic mice expressing Stat4A, an unphosphorylatable Stmn1 mutant, showed reduced contextual fear memory, and that Stmn1-MT interactions were a possible mechanism underlying age-dependent memory loss. In 2019, Nguyen et al. [54] found that Stmn1 KO mice showed anxious hyperactivity, impaired object recognition, and decreased levels of neutral and social investigating behaviors at baseline. In a recent study, Shan et al. [55] demonstrated that Stmn1 in the brain memory loop, especially the hippocampus, regulated MT structure by phosphorylation at Ser 25 and Ser 38, and was thus involved in the mediation of fear memory abnormalities in post-traumatic stress disorder (PTSD). Therefore, animal experiments support a correlation between Stmn1 and cognitive functions like learning and memory, as well as related emotions like fear.

In contrast to the animal literature, studies on Stmn1 gene function in humans are rare. Brocke et al. [24] reported that two Stmn1SNPs (rs182455 and rs213641) had significant effects on fear and anxiety responses in humans, measured by startle and cortisol stress responses. Cao et al. [56] found that the Stmn1 rs182455 genotype significantly predicted the severity of reexperiencing symptoms in female patients with PTSD. There is only one report of a direct correlation between Stmn1 gene polymorphism and cognitive function in humans. Ehlis et al. [23] found altered cognitive-affective processing in carriers of the rs182455 SNP C allele, as probed using three experimental paradigms. Of note, the SNP rs182455 selected in the present study is consistent with the SNP studied in the three previous studies [23, 24, 56]. In terms of the correlation between Stmn1 variation and human cognitive function, our findings support the previous results [23]. However, the studies differ in several ways. First, different cognitive assessment tools were used in the study by Ehlis et al. [23] and the present study, and thus different aspects of cognitive functions were studied. The previous study mainly focused on emotion regulation, whereas the present study evaluated individual ability to inhibit habitual responses and react selectively to information, as well as verbal learning and memory. Second, the samples varied in terms of race and size: 59 healthy German participants were used by Ehlis et al. [23], whereas the present study involved 129 healthy Han Chinese participants. Therefore, our findings of a direct relationship between Stmn1 gene variants and cognitive function assessed by the SCWT and HVLT-R in a Chinese sample are a confirmation and extension of previous findings.

The present study found no significant differences in SW and SCW scores on the SCWT or DR, TP and FP scores on the HVLT-R between males and females. However, SC scores on the SCWT and TR scores on the HVLT-R were significantly higher for females than for males, indicating that females have higher immediate free recall, cognitive flexibility, and ability to inhibit usual responses than males. Numerous studies have reported significant sex differences in cognitive function in different groups [57, 58, 59, 60]. Some reviews also summarized and addressed such sex specificity for cognitive functions in detail [61, 62]. Therefore, the findings of the present study that two dimensions of cognitive assessment differed between males and females are consistent with the conclusions of previous related research.

The present study also demonstrated a significant female-specific difference in the SC dimension of the SCWT among the rs182455 genotype groups (females carrying the CC genotype had significantly higher SC scores than those with the TT and CT genotypes). Further analysis showed that the difference in SC dimensions between the two sexes might derive mainly from differences in SC scores between the two sexes with the rs182455 CC genotype. This suggests that the interaction between Stmn1 variants (especially the rs182455 CC genotype) and sex could influence an individual’s cognitive function. In previous studies, Brocke et al. [24] found that the Stmn1 rs182455 genotype interacted with sex to significantly impact fear and anxiety responses, Cao et al. [56] found that the rs182455 C allele was only significantly associated with reexperiencing PTSD symptoms in females, and Ehlis et al. [23] found that the effects of the rs182455 C allele appeared more significant on altered cognitive–affective processing in females. Thus, the female-specific results on the effect of the rs182455 CC genotype on cognitive function in the present study thus support and build upon previous findings.

We speculate why SC scores were higher in females than in males and why the rs182455 CC genotype was significantly associated with SC scores in females, but not in males. As Cahill pointed out, sex differences at the level of brain organization and function are neither small nor unreliable [63]. Given the large amount of evidence that males and females differ in terms of brain regions involved in emotional regulation and cognition, as well as in several neurotransmitter systems, the influence of sex as an additional factor—as well as a factor interacting with other variables—must be considered. Another potential reason for sex-specific findings is androgens secreted by the ovaries of women, which might be involved in MT dynamics that affect neurite branch growth and synaptic plasticity, ultimately affecting biological determination of cognitive function. Regarding the observed sex effects, in silico analysis has demonstrated the transcriptional influence of rs182455 with the T allele facilitating the binding of estrogen regulated transcription factors [23]. Therefore, the interaction between sex and Stmn1 SNP genotypes might be the underlying mechanism of individual differences in cognitive ability. However, this speculation needs to be confirmed by further biochemical experiments.

In summary, this study investigated associations between Stmn1 rs182455 polymorphisms and cognitive abilities measured by the SCWT and HVLT-R in a sample of healthy Han Chinese individuals, demonstrating the underlying biogenetic mechanisms regulating cognition. The results demonstrated a significant modulating influence of SNP rs182455 on the SC dimension of the SCWT and the TR dimension of the HVLT-R, indicating that individuals with the rs182455 CC genotype have higher immediate free recall and cognitive flexibility than those with the CT or TT genotypes. A significant difference in the SC dimension of the SCWT was also observed for the rs182455 genotype in females, indicating that this association is sex-specific. These results provide supporting evidence that Stmn1 gene variations and sex impact cognitive abilities in healthy Chinese individuals and may contribute to the etiopathogenesis of many neurodegenerative and psychiatric conditions since cognitive impairment is their core symptom. Moreover, the Stmn1 protein has been known to play an important role in neurite extension and growth, which typically occur during neural development, repair, and regeneration. Next, further studies, including experiments with gene knockout animals, should be conducted to determine the exact and specific role of the Stmn1 gene and protein in cognitive function. The results of the present study and further studies will provide empirical evidence for the abnormalities of neurodevelopment and synaptic plasticity in the pathogenesis of many neuropsychiatric disorders with cognitive impairment and provide indicators and an evidence-based basis for the prevention and treatment of such disorders in the future.

However, the results of the present study should be viewed with caution because of the limited sample size and age range, the limited number of studied SNPs, and the limitations of the neurocognitive assessment tools used, which might increase the potential bias. Moreover, the present study design was a cross-sectional observational study. This design can only describe the correlation between two variables, not directly prove causation, and it is difficult for this design to completely exclude the effects of confounding factors, which may mask or exaggerate the true association between two variables. In the future, studies of rs182455 SNP and other Stmn1 gene SNPs in larger Chinese or other ethnic samples, as well as a cohort study design, are needed to verify these findings. Research on the specific mechanisms underlying the influence of Stmn1 variants on individual cognitive function is also needed to develop a more comprehensive understanding of this effect.

5. Conclusions

All in all, the present findings suggest that rs182455 Stmn1 polymorphism might affect cognitive flexibility and immediate free recall in healthy Chinese individuals, especially females.

Availability of Data and Materials

The raw data supporting the results and conclusions of this article are available upon request.

References

[1] Jarecki JB, Tan JH, Jenny MA. A framework for building cognitive process models. Psychonomic Bulletin & Review. 2020; 27: 1218–1229. https://doi.org/10.3758/s13423-020-01747-2

[2] Mukaetova-Ladinska EB, De Lillo C, Arshad Q, Subramaniam HE, Maltby J. Cognitive Assessment of Dementia: The Need for an Inclusive Design Tool. Current Alzheimer Research. 2022; 19: 265–273. https://doi.org/10.2174/1567205019666220315092008

[3] Cheon MS, Fountoulakis M, Cairns NJ, Dierssen M, Herkner K, Lubec G. Decreased protein levels of stathmin in adult brains with Down syndrome and Alzheimer’s disease. Journal of Neural Transmission. Supplementum. 2001; 281–288. https://doi.org/10.1007/978-3-7091-6262-0_23

[4] Hayashi K, Pan Y, Shu H, Ohshima T, Kansy JW, White CL, 3rd, et al. Phosphorylation of the tubulin-binding protein, stathmin, by Cdk5 and MAP kinases in the brain. Journal of Neurochemistry. 2006; 99: 237–250. https://doi.org/10.1111/j.1471-4159.2006.04113.x

[5] Li W, Zhou FC, Zhang L, Ng CH, Ungvari GS, Li J, et al. Comparison of cognitive dysfunction between schizophrenia and bipolar disorder patients: A meta-analysis of comparative studies. Journal of Affective Disorders. 2020; 274: 652–661. https://doi.org/10.1016/j.jad.2020.04.051

[6] Bouchard TJ, Jr, McGue M. Familial studies of intelligence: a review. Science (New York, N.Y.). 1981; 212: 1055–1059. https://doi.org/10.1126/science.7195071

[7] Tucker-Drob EM, Briley DA, Harden KP. Genetic and Environmental Influences on Cognition Across Development and Context. Current Directions in Psychological Science. 2013; 22: 349–355. https://doi.org/10.1177/0963721413485087

[8] Lyons MJ, Panizzon MS, Liu W, McKenzie R, Bluestone NJ, Grant MD, et al. A longitudinal twin study of general cognitive ability over four decades. Developmental Psychology. 2017; 53: 1170–1177. https://doi.org/10.1037/dev0000303

[9] Chabris CF, Hebert BM, Benjamin DJ, Beauchamp J, Cesarini D, van der Loos M, et al. Most reported genetic associations with general intelligence are probably false positives. Psychological Science. 2012; 23: 1314–1323. https://doi.org/10.1177/0956797611435528

[10] Davies G, Tenesa A, Payton A, Yang J, Harris SE, Liewald D, et al. Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Molecular Psychiatry. 2011; 16: 996–1005. https://doi.org/10.1038/mp.2011.85

[11] Ktaiche M, Fares Y, Abou-Abbas L. Stroop color and word test (SCWT): Normative data for the Lebanese adult population. Applied Neuropsychology. Adult. 2022; 29: 1578–1586. https://doi.org/10.1080/23279095.2021.1901101

[12] Kane MJ, Engle RW. Working-memory capacity and the control of attention: the contributions of goal neglect, response competition, and task set to Stroop interference. Journal of Experimental Psychology. General. 2003; 132: 47–70. https://doi.org/10.1037/0096-3445.132.1.47

[13] Periáñez JA, Lubrini G, García-Gutiérrez A, Ríos-Lago M. Construct Validity of the Stroop Color-Word Test: Influence of Speed of Visual Search, Verbal Fluency, Working Memory, Cognitive Flexibility, and Conflict Monitoring. Archives of Clinical Neuropsychology: the Official Journal of the National Academy of Neuropsychologists. 2021; 36: 99–111. https://doi.org/10.1093/arclin/acaa034

[14] Benedict RHB, Schretlen D, Groninger L, Brandt J. Hopkins Verbal Learning Test – Revised: Normative Data and Analysis of Inter-Form and Test-Retest Reliability. Clinical Neuropsychologist. 1998; 12: 43–55. https://doi.org/10.1076/clin.12.1.43.1726

[15] Shi J, Tian J, Wei M, Miao Y, Wang Y. The utility of the Hopkins Verbal Learning Test (Chinese version) for screening dementia and mild cognitive impairment in a Chinese population. BMC Neurology. 2012; 12: 136. https://doi.org/10.1186/1471-2377-12-136

[16] McLaughlin NCR, Chang AC, Malloy P. Verbal and nonverbal learning and recall in dementia with lewy bodies and Alzheimer’s disease. Applied Neuropsychology. Adult. 2012; 19: 86–89. https://doi.org/10.1080/09084282.2011.643944

[17] Gaines JJ, Shapiro A, Alt M, Benedict RHB. Semantic clustering indexes for the Hopkins Verbal Learning Test-Revised: initial exploration in elder control and dementia groups. Applied Neuropsychology. 2006; 13: 213–222. https://doi.org/10.1207/s15324826an1304_2

[18] Harrie A, Hampstead BM, Lewis C, Herreshoff E, Kotagal V. Cognitive correlates of dual tasking costs on the timed up and go test in Parkinson disease. Clinical Parkinsonism & Related Disorders. 2022; 7: 100158. https://doi.org/10.1016/j.prdoa.2022.100158

[19] Hogervorst E, Combrinck M, Lapuerta P, Rue J, Swales K, Budge M. The Hopkins Verbal Learning Test and screening for dementia. Dementia and Geriatric Cognitive Disorders. 2002; 13: 13–20. https://doi.org/10.1159/000048628

[20] Shapiro AM, Benedict RH, Schretlen D, Brandt J. Construct and concurrent validity of the Hopkins Verbal Learning Test-revised. The Clinical Neuropsychologist. 1999; 13: 348–358. https://doi.org/10.1076/clin.13.3.348.1749

[21] Shumyatsky GP, Malleret G, Shin RM, Takizawa S, Tully K, Tsvetkov E, et al. stathmin, a gene enriched in the amygdala, controls both learned and innate fear. Cell. 2005; 123: 697–709. https://doi.org/10.1016/j.cell.2005.08.038

[22] Peschanski M, Hirsch E, Dusart I, Doye V, Marty S, Manceau V, et al. Stathmin: cellular localization of a major phosphoprotein in the adult rat and human CNS. The Journal of Comparative Neurology. 1993; 337: 655–668. https://doi.org/10.1002/cne.903370410

[23] Ehlis AC, Bauernschmitt K, Dresler T, Hahn T, Herrmann MJ, Röser C, et al. Influence of a genetic variant of the neuronal growth associated protein Stathmin 1 on cognitive and affective control processes: an event-related potential study. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics: the Official Publication of the International Society of Psychiatric Genetics. 2011; 156B: 291–302. https://doi.org/10.1002/ajmg.b.31161

[24] Brocke B, Lesch KP, Armbruster D, Moser DA, Müller A, Strobel A, et al. Stathmin, a gene regulating neural plasticity, affects fear and anxiety processing in humans. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics: the Official Publication of the International Society of Psychiatric Genetics. 2010; 153B: 243–251. https://doi.org/10.1002/ajmg.b.30989

[25] Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods. 2007; 39: 175–191. https://doi.org/10.3758/bf03193146

[26] Stroop JR. Studies of interference in serial verbal reactions. Journal of Experimental Psychology. 1935; 18: 643–662. https://doi.org/10.1037/h0054651

[27] Golden CJ. Identification of brain disorders by the Stroop Color and Word Test. Journal of Clinical Psychology. 1976; 32: 654–658. https://doi.org/10.1002/1097-4679(197607)32:3<654::aid-jclp2270320336>3.0.co;2-z

[28] Wecker NS, Kramer JH, Wisniewski A, Delis DC, Kaplan E. Age effects on executive ability. Neuropsychology. 2000; 14: 409–414. https://doi.org/10.1037//0894-4105.14.3.409

[29] Brandt J. The hopkins verbal learning test: Development of a new memory test with six equivalent forms. Clinical Neuropsychologist. 1991; 5: 125–142. https://doi.org/10.1080/13854049108403297

[30] Ryan J, Woods RL, Murray AM, Shah RC, Britt CJ, Reid CM, et al. Normative performance of older individuals on the Hopkins Verbal Learning Test-Revised (HVLT-R) according to ethno-racial group, gender, age and education level. The Clinical Neuropsychologist. 2021; 35: 1174–1190. https://doi.org/10.1080/13854046.2020.1730444

[31] Ma H, Huang Y, Zhang B, Jin L, Cong Z, Wang Y, et al. Neurotensin receptor 1 gene polymorphisms are associated with personality traits in healthy Chinese individuals. Neuropsychobiology. 2014; 69: 11–18. https://doi.org/10.1159/000356966

[32] Ma H, Huang Y, Zhang B, Li J, Wang Y, Zhao X, et al. Association between neurotensin receptor 1 (NTR1) gene polymorphisms and schizophrenia in a Han Chinese population. Journal of Molecular Neuroscience: MN. 2013; 50: 345–352. https://doi.org/10.1007/s12031-013-9988-5

[33] Ma H, Huang Y, Zhang B, Wang Y, Zhao H, Du H, et al. Association between neurotensin receptor 1 gene polymorphisms and alcohol dependence in a male Han Chinese population. Journal of Molecular Neuroscience: MN. 2013; 51: 408–415. https://doi.org/10.1007/s12031-013-0041-5

[34] Lencz T, Knowles E, Davies G, Guha S, Liewald DC, Starr JM, et al. Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT). Molecular Psychiatry. 2014; 19: 168–174. https://doi.org/10.1038/mp.2013.166

[35] Benyamin B, Pourcain B, Davis OS, Davies G, Hansell NK, Brion MJA, et al. Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Molecular Psychiatry. 2014; 19: 253–258. https://doi.org/10.1038/mp.2012.184

[36] Kirkpatrick RM, McGue M, Iacono WG, Miller MB, Basu S. Results of a “GWAS plus”: general cognitive ability is substantially heritable and massively polygenic. PloS One. 2014; 9: e112390. https://doi.org/10.1371/journal.pone.0112390

[37] Davies G, Armstrong N, Bis JC, Bressler J, Chouraki V, Giddaluru S, et al. Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53949). Molecular Psychiatry. 2015; 20: 183–192. https://doi.org/10.1038/mp.2014.188

[38] Trampush JW, Yang MLZ, Yu J, Knowles E, Davies G, Liewald DC, et al. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium. Molecular Psychiatry. 2017; 22: 336–345. https://doi.org/10.1038/mp.2016.244

[39] Sniekers S, Stringer S, Watanabe K, Jansen PR, Coleman JRI, Krapohl E, et al. Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nature Genetics. 2017; 49: 1107–1112. https://doi.org/10.1038/ng.3869

[40] Davies G, Lam M, Harris SE, Trampush JW, Luciano M, Hill WD, et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nature Communications. 2018; 9: 2098. https://doi.org/10.1038/s41467-018-04362-x

[41] Chauvin S, Sobel A. Neuronal stathmins: a family of phosphoproteins cooperating for neuronal development, plasticity and regeneration. Progress in Neurobiology. 2015; 126: 1–18. https://doi.org/10.1016/j.pneurobio.2014.09.002

[42] Charbaut E, Curmi PA, Ozon S, Lachkar S, Redeker V, Sobel A. Stathmin family proteins display specific molecular and tubulin binding properties. The Journal of Biological Chemistry. 2001; 276: 16146–16154. https://doi.org/10.1074/jbc.M010637200

[43] Rana S, Maples PB, Senzer N, Nemunaitis J. Stathmin 1: a novel therapeutic target for anticancer activity. Expert Review of Anticancer Therapy. 2008; 8: 1461–1470. https://doi.org/10.1586/14737140.8.9.1461

[44] Belmont LD, Mitchison TJ. Identification of a protein that interacts with tubulin dimers and increases the catastrophe rate of microtubules. Cell. 1996; 84: 623–631. https://doi.org/10.1016/s0092-8674(00)81037-5

[45] Uchida S, Shumyatsky GP. Deceivingly dynamic: Learning-dependent changes in stathmin and microtubules. Neurobiology of Learning and Memory. 2015; 124: 52–61. https://doi.org/10.1016/j.nlm.2015.07.011

[46] Curmi PA, Andersen SS, Lachkar S, Gavet O, Karsenti E, Knossow M, et al. The stathmin/tubulin interaction in vitro. The Journal of Biological Chemistry. 1997; 272: 25029–25036. https://doi.org/10.1074/jbc.272.40.25029

[47] Beretta L, Dobránsky T, Sobel A. Multiple phosphorylation of stathmin. Identification of four sites phosphorylated in intact cells and in vitro by cyclic AMP-dependent protein kinase and p34cdc2. The Journal of Biological Chemistry. 1993; 268: 20076–20084.

[48] Bliss TVP, Collingridge GL, Morris RG, Reymann KG. Long-term potentiation in the hippocampus: Discovery, mechanisms and function. Neuroforum. 2018; 24: A103–A120. https://doi.org/10.1515/nf-2017-A059

[49] Bin Ibrahim MZ, Benoy A, Sajikumar S. Long-term plasticity in the hippocampus: maintaining within and ’tagging’ between synapses. The FEBS Journal. 2022; 289: 2176–2201. https://doi.org/10.1111/febs.16065

[50] Whitlock JR, Heynen AJ, Shuler MG, Bear MF. Learning induces long-term potentiation in the hippocampus. Science (New York, N.Y.). 2006; 313: 1093–1097. https://doi.org/10.1126/science.1128134

[51] Lynch MA. Long-term potentiation and memory. Physiological Reviews. 2004; 84: 87–136. https://doi.org/10.1152/physrev.00014.2003

[52] Martel G, Nishi A, Shumyatsky GP. Stathmin reveals dissociable roles of the basolateral amygdala in parental and social behaviors. Proceedings of the National Academy of Sciences of the United States of America. 2008; 105: 14620–14625. https://doi.org/10.1073/pnas.0807507105

[53] Uchida S, Martel G, Pavlowsky A, Takizawa S, Hevi C, Watanabe Y, et al. Learning-induced and stathmin-dependent changes in microtubule stability are critical for memory and disrupted in ageing. Nature Communications. 2014; 5: 4389. https://doi.org/10.1038/ncomms5389

[54] Nguyen TB, Prabhu VV, Piao YH, Oh YE, Zahra RF, Chung YC. Effects of Stathmin 1 Gene Knockout on Behaviors and Dopaminergic Markers in Mice Exposed to Social Defeat Stress. Brain Sciences. 2019; 9: 215. https://doi.org/10.3390/brainsci9090215

[55] Shan W, Han F, Xu Y, Shi Y. Stathmin Regulates Spatiotemporal Variation in the Memory Loop in Single-Prolonged Stress Rats. Journal of Molecular Neuroscience: MN. 2020; 70: 576–589. https://doi.org/10.1007/s12031-019-01459-w

[56] Cao C, Wang L, Wang R, Dong C, Qing Y, Zhang X, et al. Stathmin genotype is associated with reexperiencing symptoms of posttraumatic stress disorder in Chinese earthquake survivors. Progress in Neuro-psychopharmacology & Biological Psychiatry. 2013; 44: 296–300. https://doi.org/10.1016/j.pnpbp.2013.04.004

[57] Eissman JM, Dumitrescu L, Mahoney ER, Smith AN, Mukherjee S, Lee ML, et al. Sex differences in the genetic architecture of cognitive resilience to Alzheimer’s disease. Brain: a Journal of Neurology. 2022; 145: 2541–2554. https://doi.org/10.1093/brain/awac177

[58] Dao E, Barha CK, Santos M, Welch M, Liu-Ambrose T. Sex Differences in the Relationship Between Arterial Stiffness and Cognitive Function in Older Adults. Journal of Stroke and Cerebrovascular Diseases: the Official Journal of National Stroke Association. 2022; 31: 106175. https://doi.org/10.1016/j.jstrokecerebrovasdis.2021.106175

[59] Reekes TH, Higginson CI, Ledbetter CR, Sathivadivel N, Zweig RM, Disbrow EA. Sex specific cognitive differences in Parkinson disease. NPJ Parkinson’s Disease. 2020; 6: 7. https://doi.org/10.1038/s41531-020-0109-1

[60] Zhou T, Guo J, Zhang J, Xiao H, Qi X, Wu C, et al. Sex-Specific Differences in Cognitive Abilities Associated with Childhood Cadmium and Manganese Exposures in School-Age Children: a Prospective Cohort Study. Biological Trace Element Research. 2020; 193: 89–99. https://doi.org/10.1007/s12011-019-01703-9

[61] Ferretti MT, Iulita MF, Cavedo E, Chiesa PA, Schumacher Dimech A, Santuccione Chadha A, et al. Sex differences in Alzheimer disease - the gateway to precision medicine. Nature Reviews. Neurology. 2018; 14: 457–469. https://doi.org/10.1038/s41582-018-0032-9

[62] Hilz EN, Gore AC. Sex-specific Effects of Endocrine-disrupting Chemicals on Brain Monoamines and Cognitive Behavior. Endocrinology. 2022; 163: bqac128. https://doi.org/10.1210/endocr/bqac128

[63] Canli T, Qiu M, Omura K, Congdon E, Haas BW, Amin Z, et al. Neural correlates of epigenesis. Proceedings of the National Academy of Sciences of the United States of America. 2006; 103: 16033–16038. https://doi.org/10.1073/pnas.0601674103

Funding

Hainan Province Clinical Medical Center

Scientific Research Fund of National Natural Science Foundation of China(81771438)

Leading Talent Program of Hainan Medical University(RZ2300007451)

Science and Technology Special Fund of Hainan Province(ZDYF2024SHFZ073)