Abstract
Bipolar disorder is a chronic disorder characterized by fluctuations in mood state and energy and recurrent episodes of mania/hypomania and depression. Bipolar disorder may be regarded as a neuro-progressive disorder in which repeated mood episodes may lead to cognitive decline and dementia development. In the current review, we employed genome-wide association studies to comprehensively investigate the genetic variants associated with bipolar disorder and dementia. Thirty-nine published manuscripts were identified: 20 on bipolar disorder and 19 on dementia. The results showed that the genes CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A were overlapping between patients with bipolar disorder and dementia. In conclusion, the genes CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A may be associated with the neuro-progression of bipolar disorder to dementia. Further genetic studies are needed to comprehensively clarify the role of genes in cognitive decline and the development of dementia in patients with bipolar disorder.
Introduction
Bipolar disorder is a chronic disorder characterized by fluctuations in mood state and energy, in addition to recurrent episodes of mania/hypomania and depression (1). Cognitive impairment has been documented in a variety of neuropsychological domains during the mood disturbances associated with the acute episodes of bipolar disorder (2, 3). However, patients with bipolar disorder suffer from cognitive impairment not only during the acute phase but also during the remission phase (4, 5). Bipolar disorder in the first episode is associated with widespread cognitive dysfunction, especially in psychomotor speed, attention, working memory, and cognitive flexibility, suggesting that a broad range of cognitive deficits is already present at this early stage (6). Cognitive decline occurs with repeated manic episodes, hospitalizations, and length of illness in patients with bipolar disorder, suggesting that the recurrence of mania may have a long-term neuropsychological impact (7, 8). Studies on bipolar disorder have shown that neuropsychological deficits are detectable in euthymia, and they contribute to poor outcomes (8, 9). Patients with bipolar disorder have the greatest risk of dementia, followed by those with unipolar depression, schizophrenia, and neurosis (10). A meta-analysis revealed that a history of bipolar disorder significantly increased the risk of dementia (odds ratio: 2.36; 95% CI: 1.36–4.09) (11). Another meta-analysis showed that bipolar disorder increases the risk of dementia (odds ratio: 2.96; 95% CI: 2.09–4.18), and the risk of progression to dementia is higher in bipolar disorder than that in major depressive disorder (12). Thus, bipolar disorder may be seen as a neuro-progressive disorder in which repeated mood episodes may lead to cognitive decline and, finally, the development of dementia.
Genome-wide association studies (GWAS) aim to identify single nucleotide polymorphisms (SNPs) in which allele frequencies vary systematically as a function of phenotypic trait values (13). The identification of trait-associated SNPs distributed throughout the genome may provide new insights into the biological mechanisms underlying psychiatric disorders (13). To date, GWAS have successfully identified SNPs associated with the risk of bipolar disorder and dementia (14, 15). The clinical question arises as to which genetic factors are associated with the association between bipolar disorder and dementia. From a clinical perspective, we previously hypothesized that there is a specific group of patients whose diagnoses longitudinally change from depression to bipolar disorder and finally to dementia, and the glycogen synthase kinase 3β gene may be a common etiological factor in these diseases and diagnostic conversions (16). In the current review, using a completely different perspective, we employed the results of GWAS to comprehensively investigate genetic variants associated with bipolar disorder and dementia (including Alzheimer’s disease, Lewy body dementia, frontotemporal dementia, and vascular dementia).
Methods
This review was qualitative and not systematic in nature. This study was conducted in January, 2024. Using the PubMed database, we conducted searches with keywords “bipolar disorder” and “GWAS”, “dementia” and “GWAS”. In this review, only GWAS that examined the relationship between the diagnosis of bipolar disorder or dementia and genes and SNPs were included. Articles that were not GWAS or were written in languages other than English were excluded. We simply examined the presence of overlapping genes and SNPs reported in patients with bipolar disorder and dementia.
Results
Thirty-nine published manuscripts were identified: 20 on bipolar disorder (14, 17–35) and 19 on dementia (15, 36–53) (see Supplementary Figure 1 for the literature screening flow chart). Table 1 summarizes the characteristics of the included studies. The lists of significant SNPs and genes associated with bipolar disorder and dementia reported by GWAS are provided in Supplementary Tables 1, 2, respectively.
Table 1
| Author | Diagnosis | Criteria | Sample size | Platform | GWAS software |
|---|---|---|---|---|---|
| Mullins et al., 2021 (14) | Bipolar disorder | DSM-IV, ICD-9, ICD-10 | Bipolar disorder: 41,917, Controls:371,549 | Affymetrix and Illumina | PLINK ver 1.90 |
| Li et al., 2021 (17) | Bipolar disorder | DSM-IV | Bipolar disorder: 1784, Controls:2474 | SNaPShot | PLINK ver 1.9 |
| Budde et al., 2019 (18) | Bipolar disorder | DSM-IV | Bipolar disorder:1,081 | Illumina; HumanHap550v3, Human610, Human660w | PLINK |
| Stahl et al., 2019 (19) | Bipolar disorder | DSM-IV or ICD-10 | Bipolar disorder:20,352, Controls:31,358 | Affymetrix and Illumina | PLINK ver 1.09 |
| Ikeda et al., 2018 (20) | Bipolar disorder | DSM-IV-TR | Bipolar disorder: 2,964, Controls:61,887 | Illumina; HumanOmniExpressExome v1.0/v1.2 chip |
LocusZoom |
| Acikel et al., 2016 (21) | Bipolar disorder | – | Bipolar disorder: 604, Controls: 1,767 | Affymetrix; Affy6.0 | PLINK ver 1.8 |
| Hou et al., 2016 (22) | Bipolar disorder | DSM-III or DSM-IV | Bipolar disorder: 9784, Controls:30,471 | Affymetrix; Affy6.0, 500K and Illumina; HumanHap550, HumanOmni2.5M, OmniExpress | PLINK |
| Li et al., 2016 (23) | Bipolar disorder | DSM-IV, ICD-10 | Bipolar disorder: 7,481, Controls: 9,250 | Affymetrix exon arrays | Sherlock |
| Kuo et al., 2014 (24) | Bipolar disorder | DSM-IV | Bipolar disorder: 240, Controls: 240 | Affymetrix; Affy6.0 | PLINK ver 1.07 |
| Mühleisen et al., 2014 (25) | Bipolar disorder | DSM-IIR, DSM-IV | Bipolar disorder: 9,747, Controls:14,278 | Illumina; Human660W, HumanOmni1 | PLINK ver 1.07, INTERSNP ver 1.11 |
| Xu et al., 2014 (26) | Bipolar disorder | DSM-IV or ICD-10 | Bipolar disorder: 950, Controls: 950 | Affymetrix; Affy5.0 | PLINK |
| Chen et al., 2013 (27) | Bipolar disorder | DSM-IV | Bipolar disorder: 7773, Controls:10 915 | Affymetrix; Affy6.0, 500K and Illumina; HumanHap550, HumanHap300, human 610-Quad, Infinium II |
PLINK ver 1.4 |
| Green et al., 2013 (28) | Bipolar disorder | DSM-IV | Bipolar disorder: 7,481, Controls: 9,250 | Illumina | PLINK ver 1.07 |
| Cichon et al., 2011 (29) | Bipolar disorder | DSM-IV | Bipolar disorder: 682, Controls:1,300 | Illumina; HumanHap550v3 | PLINK ver 1.05 |
| Lee et al., 2011 (30) | Bipolar disorder | DSM-IV | Bipolar disorder: 1409, Controls: 2000 | Illumina; HumanHap550 | – |
| Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011 (31) | Bipolar disorder | DSM-IV, ICD-10 | Bipolar disorder: 11,974, Controls: 51,792 | Affymetrix; Affy6.0, Affy5.0, 500K and Illumina; HumanHap550 | PLINK |
| Yosifova et al., 2011 (32) | Bipolar disorder | – | Bipolar disorder: 188, Controls: 376 | Illumina; HumanHap550v3 | – |
| Djurovic et al., 2010 (33) | Bipolar disorder | DSM-IV | Bipolar disorder: 194, Controls:336 | Affymetrix; Affy6.0 and Illumina; HumanHap300 and HumanCNV370 |
PLINK |
| Scott et al., 2009 (34) | Bipolar disorder | DSM-IV or ICD-10 | Bipolar disorder: 3,683, Controls:14,507 | Affymetrix; 500K and Illumina; HumanHap550 | – |
| Ferreira et al., 2008 (35) | Bipolar disorder | DSM-IV | Bipolar disorder: 4,387, Controls: 6,209 | Affymetrix; Affy6.0, Affy5.0, 500K | PLINK |
| Dalmasso et al., 2024 (36) | Alzheimer’s disease | NINCDS-ADRDA | Alzheimer’s disease: 539, Controls: 854 | Illumina; Infinium Global Screening Array v.1.0 | PLINK ver 1.9 |
| Sherva et al., 2023 (37) | Alzheimer’s disease | ICD-9, ICD-10 | Alzheimer’s disease: 4,012, Controls: 18,435 | MVP 1.0 custom Axiom array | SHAPEIT4 v 4.1.3, MINIMAC4 |
| Bellenguez et al., 2022 (15) | Alzheimer’s disease | NINCDS–ADRDA | Alzheimer’s disease:111,326, Controls:677,663 | Affymetrix; 500K and Illumina; Human Omni Express-24 v1.1, Human 610, HumanHap550 | SNPTEST 2.5.4-beta3, PLINK v1.90 |
| Harper et al., 2022 (38) | Alzheimer’s disease | – | Alzheimer’s disease: 424, Controls: 2,206 | Illumina;Infinium Multi-Ethnic Global-8 v1.0 | PLINK |
| Wightman et al., 2021 (39) | Alzheimer’s disease | NINCDS–ADRDA, ICD-9, ICD-10 | Alzheimer’s disease: 90,338, Controls:1,036,225 | Illumina; HumanHap550, Human Omni Express, Infinium Global Screening Array | PLINK ver 1.90 |
| Jansen et al., 2019 (40) | Alzheimer’s disease | NINCDS–ADRDA, ICD-10 | Alzheimer’s disease:71,880, Controls:383,378 | Affymetrix;UK BiLEVE, Illumina; Human Omni Express-24 v.1.1 Axiom array, UK Biobank Axiom array |
PLINK |
| Kunkle et al., 2019 (41) | Alzheimer’s disease | NINCDS-ADRDA, DSM-IV, DSM-V | Alzheimer’s disease: 35,274, Controls:59,163 | Affymetrix; 500K and Illumina; HumanHap550, 370CNV Duo, Human 610, OmniExpress | PLINK |
| Moreno-Grau et al., 2019 (42) | Alzheimer’s disease | – | Alzheimer’s disease: 11,999, Controls: 9,236 | Affymetrix | PLINK ver 1.9 |
| Witoelar et al., 2018 (43) | Alzheimer’s disease | ICD-10 | Alzheimer’s disease: 2,135, Controls:6,858 | Illumina; Human Omni Express-24 v.1.1 | PLINK ver 1.9 |
| Jun et al., 2016 (44) | Alzheimer’s disease | NINCDS-ADRDA | Alzheimer’s disease: 17,536, Controls: 3,6175 | Affymetrix; Affy6.0, Illumina; Human Omni Express-24 | – |
| Lambert et al., 2013 (45) | Alzheimer’s disease | NINCDS-ADRDA | Alzheimer’s disease: 17,008, Controls:37,154 | Illumina; HumanHap550, 370CNV Duo, Human 610, Omni1 | PLINK, probABEL, R (GEE), SNPtest |
| Seshadri et al., 2010 (46) | Alzheimer’s disease | NINCDS-ADRDA/DSM-IV | Alzheimer’s disease: 3,006, Controls:14,642 | Illumina; HumanHap550, 370CNV Duo, Human 610 | PLINK |
| Mukherjee et al., 2020 (47) | Late-onset Alzheimer’s disease | NINCDS–ADRDA | Late-onset Alzheimer’s disease: 2431, Controls:3447 | – | PLINK ver 1.9 |
| Beecham et al., 2009 (48) | Late-onset Alzheimer’s disease | NINCDS–ADRDA | Late-onset Alzheimer’s disease: 492, Controls:496 | Illumina; HumanHap550 | PLINK ver 1.9 |
| Chia et al., 2021 (49) | Lewy body dementia | Established consensus criteria of DLB Consortium | Lewy body dementia: 2591, Controls:4027 | Illumina; HiSeq X Ten sequencer | PLINK ver 1.9 |
| Schrijvers et al., 2012 (50) | Vascular dementia | NINDS-AIREN | Vascular dementia: 67, Controls:5633 | Illumina; HumanHap550 v3.0 | PLINK |
| Reus et al., 2021 (51) | Frontotemporal dementia | Neary criteria, Rascovsky and Gorno-Tempini criteria | Frontotemporal dementia: 354, Controls: 4,209 | Illumina; Genome Screening Array | PLINK ver 2.0 |
| Ferrari et al., 2015 (52) | Frontotemporal dementia | Neary criteria, Rascovsky and Gorno-Tempini criteria | Frontotemporal dementia: 530, Controls:926 | Illumina; Human 660K | PLINK |
| Ferrari et al., 2014 (53) | Frontotemporal dementia | Neary criteria | Frontotemporal dementia: 3526, Controls:9402 | Illumina; Human 370K, 550K, 660K | PLINK ver 1.07 |
The characteristics of the studies included in the present review.
DSM, Diagnostic and Statistical Manual of Mental Disorders; ICD, International Classification of Diseases; NINCDS-ADRDA, National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association; NINDS-AIREN, Neurological Disorders and Stroke-Association Internationale pour la Recherche et l'Enseignement en Neurosciences.
A review revealed that among the genes reported to be associated with the diagnosis of bipolar disorder or dementia in previous GWAS studies, the overlapping gene was calcium voltage-gated channel subunit Alpha1 C (CACNA1C), gamma-aminobutyric acid B receptor 2 (GABBR2), sodium voltage-gated channel Alpha subunit 2 (SCN2A), cathepsin H (CTSH), methionine sulfoxide reductase A (MSRA), and SH3 and PX domains 2A (SH3PXD2A) (Table 2; Supplementary Figure 2). With respect to the type of dementia, rs11062164 of CACNA1C, rs16916777 of GABBR2, and rs17738042 of SH3PXD2A are associated with vascular dementia; rs10184275 and rs2119067 of SCN2A are associated with late-onset Alzheimer’s disease; and, rs12592898 of CTSH and rs4607615 of MSRA are associated with Alzheimer’s disease. No SNPs were found to be reported as associated with both the diagnosis of bipolar disorder and dementia.
Table 2
| Diagnosis | SNPs | Position | Minor Alleles | Allele Directions | Author |
|---|---|---|---|---|---|
| Gene: CACNA1C | |||||
| Bipolar disorder | rs1006737 | chr12:2236129 | A | + | Chen et al., 2013 (27); Ferreira et al., 2008 (35); Green et al., 2013 (28) |
| Bipolar disorder | rs1024582 | chr12:2293080 | A | + | Ferreira et al., 2008 (35) |
| Bipolar disorder | rs10744560 | chr12:2277933 | T | + | Stahl et al., 2019 (19) |
| Bipolar disorder | rs10848642 | chr12:2222406 | G | – | Chen et al., 2013 (27) |
| Bipolar disorder | rs11062170 | chr12:2239678 | C | + | Mullins et al., 2021 (14) |
| Bipolar disorder | rs4765913 | chr12:2310730 | A | + | Green et al., 2013 (28); Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011 (31) |
| Vascular dementia | rs11062164 | chr12:2224486 | A | + | Schrijvers et al., 2012 (50) |
| Gene: GABBR2 | |||||
| Bipolar disorder | rs7864144 | chr9:98643756 | G | – | Xu et al., 2014 (26) |
| Vascular dementia | rs16916777 | chr9:98518893 | A | + | Schrijvers et al., 2012 (50) |
| Gene: SCN2A | |||||
| Bipolar disorder | rs17183814 | chr2:165295879 | G | + | Mullins et al., 2021 (14); Stahl et al., 2019 (19) |
| Late-onset Alzheimer’s disease | rs10184275 | chr2:165271418 | – | – | Beecham et al., 2009 (48) |
| Late-onset Alzheimer’s disease | rs2119067 | chr2:165270773 | – | – | Beecham et al., 2009 (48) |
| Gene: CTSH | |||||
| Bipolar disorder | rs16970287 | chr15:78935915 | G | + | Yosifova et al., 2011 (32) |
| Bipolar disorder | rs2289700 | chr15:78932341 | A | + | Yosifova et al., 2011 (32) |
| Alzheimer’s disease | rs12592898 | chr15:78936857 | A | – | Bellenguez et al., 2022 (15) |
| Gene: MSRA | |||||
| Bipolar disorder | rs3088186 | chr8:10368845 | T | + | Mullins et al., 2021 (14) |
| Alzheimer’s disease | rs4607615 | chr8:10422116 | C | – | Sherva et al., 2023 (37) |
| Gene: SH3PXD2A | |||||
| Bipolar disorder | rs2281587 | chr10:103617592 | C | + | Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011 (31) |
| Vascular dementia | rs17738042 | chr10:103596274 | A | + | Schrijvers et al., 2012 (50) |
The overlapping genes and single nucleotide polymorphisms with bipolar disorder and dementia.
CACNA1C, Calcium voltage-gated channel subunit Alpha1 C; CTSH, Cathepsin H; GABBR2, Gamma-aminobutyric acid B receptor 2; GWAS, Genome-wide association studies; MSRA, Methionine sulfoxide reductase A; SH3PXD2A, SH3 and PX domains 2A; SNPs, Single nucleotide polymorphisms; SCN2A ,Sodium voltage-gated channel Alpha subunit 2.
Discussion
According to GWAS, the CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A genes were common between bipolar disorder and dementia.
CACNA1C encodes the alpha-1 subunit of the voltage-dependent L-type calcium channel expressed in the human brain (54), which regulates cellular calcium influx and is essential for normal brain development and plasticity (55). Variants of CACNA1C have been associated with bipolar disorder and several neuropsychiatric disorders, such as schizophrenia, major depressive disorder, autism spectrum disorder, attention deficit hyperactivity disorder, and substance-use disorders (56). The CACNA1C gene (especially the rs1006737 A allele) is robustly associated with bipolar disorder and might be crucial in molecular biological research on the set of interacting proteins involved in the calcium channel activity in bipolar disorder (57). The CACNA1C gene may not only be associated with the onset of bipolar disorder but also potentially affects the course of cognitive function and brain imaging. The rs1006737 variant (minor allele: A) of the CACNA1C gene is associated with cognitive impairment in patients with bipolar disorder and schizophrenia spectrum (58). Furthermore, a 2-year longitudinal study on bipolar disorder revealed that patients with the AA genotype of rs1006737 showed poorer cognitive performance, particularly in terms of processing speed (59). The rs10466907 variant of CACNA1C is associated with cognitive recovery after a major depressive episode in bipolar disorder (60). CACNA1C is expressed throughout the mouse brain, including key limbic regions relevant for emotion and cognition, such as the prefrontal cortex, hippocampus, and amygdala (61). Moreover, embryonic deletion of CACNA1C in glutamatergic neurons in the forebrain promotes the manifestation of endophenotypes related to psychiatric disorders, including cognitive decline, impaired synaptic plasticity, reduced sociability, hyperactivity, and increased anxiety (61). In a human brain study on bipolar disorder, the rs1006737 A allele of the CACNA1C gene was associated with gray matter volume, functional connectivity within the corticolimbic frontotemporal neural system, and mean thickness of cortical brain areas (62, 63). Patients with bipolar disorder carrying the rs1006737 A allele showed age-related cortical thinning of the left caudal anterior cingulate cortex (64). In contrast, among non-A carriers, age did not affect cortical thinning in the left caudal anterior cingulate cortex, suggesting an underlying relationship with aging-associated cognitive decline (64). Furthermore, tau phosphorylation is known to increase in the cerebrospinal fluid (CSF) in patients with Alzheimer’s disease (65), and the rs1006737 variant of CACNA1C is significantly associated with hyperphosphorylated tau/total tau ratio in the CSF of patients with bipolar disorder (66). A study on late-onset Alzheimer’s disease focusing on protein–protein network interactions revealed eight genes with strong associations: APOE, SORL1, APOC1, CD33, CLU, TOMM40, CNTNAP2, and CACNA1C (67). Interestingly, CACNA1C (rs10848683 variant) is also associated with ischemic stroke (68). Similarly, CACNA1C (rs11062164 variant) was significantly associated with vascular dementia (50). Thus, CACNA1C is associated with dementia. Furthermore, the rs7297582 T allele of CACNA1C is associated with a risk of bipolar disorder and poor cognitive performance (69). Although no studies have reported an association between rs7297582 and dementia, future studies should consider SNPs of interest in relation to both bipolar disorder and dementia. In the present review, the SNPs of CACNA1C did not match across studies. CACNA1C, especially rs1006737 and rs7297582, may be strongly associated with the onset of bipolar disorder, cognitive decline in bipolar disorder, and dementia.
Human gamma-aminobutyric acid type B receptor (GABABR) is a G protein-coupled receptor central to inhibitory neurotransmission in the brain (70). GABABR is assembled by the heterodimeric interaction of the intracellular C-terminal tails of the two subunits encoded by GABBR1 and GABBR2 (70). In patients with bipolar disorder, GABAergic hypofunction has been observed in the cerebellum (71). Additionally, a post-mortem study revealed reduced protein expressions of GABBR1 and GABBR2 in the cerebellum of patients with bipolar disorder (72). Dysfunction of the GABAergic system may cause cognitive impairment in humans (73). The reduction in GABAergic system components in the brain and lower GABA levels in the CSF of patients with Alzheimer’s disease suggest that the GABAergic system is vulnerable to Alzheimer’s disease pathology and should be considered a potential target for developing pharmacological strategies and novel Alzheimer’s disease biomarkers (74, 75). GABBR2 is also associated with bipolar disorder and dementia.
SCN2A encodes the voltage-gated sodium channel Nav1.2, a major central nervous system sodium channel that plays a role in the initiation and conduction of action potentials (76). SCN2A variants are associated with a range of disorders including autism spectrum disorder, developmental delay, seizures, and epileptic encephalopathy (77). Furthermore, SCN2A is associated with psychiatric disorders such as bipolar disorder and schizophrenia (14, 78). SCN2A contributes to excitability that facilitates synapse formation and development (79). A study on Alzheimer’s disease focusing on protein-protein network interactions revealed six hub genes: SCN2A, SNAP25, GRIN2A, GRIN2B, DLG2, and ATP2B2 (80). Thus, SCN2A is associated with bipolar disorder and dementia.
CTSH is a cysteine cathepsin that primarily acts as an aminopeptidase (81). The main function of cathepsins is to degrade proteins via proteolysis in lysosomes (81). CTSH has been implicated in the cis-regulated mRNA association with Alzheimer’s disease (82). CTSH expression is significantly lower in the brain tissue of healthy controls than in patients with Alzheimer’s disease (83). Moreover, CTSH knockout affected genes related to endocytosis and significantly increased Aβ42 phagocytosis in microglial cells (83). The CTSH gene was significantly associated with Alzheimer’s disease (83). The mechanism by which CTSH is associated with bipolar disorder is unknown; however, a GWAS conducted by Yosifova et al. in a Bulgarian population identified a significant association between bipolar disorder and CTSH (32). Therefore, CTSH is a gene of interest related to bipolar disorder and dementia.
MSRA has been postulated to act as a catalytic antioxidant system that protects against oxidative stress-induced cell injury and is highly expressed in the brain (84, 85). The methionine sulfoxide reductase system may contribute to the development of aging-associated diseases, including neurodegenerative diseases (86). MRSA knockout mice exhibit enhanced neurodegeneration in the brain hippocampus compared to their wild-type counterparts (86). There are hypotheses suggesting that oxidative stress is associated with bipolar disorder and Alzheimer’s disease (87, 88). The rs4840463 polymorphism in MRSA is associated with an increased risk of bipolar I and executive function defects (87). In this review, the rs3088186 polymorphism is associated with bipolar disorder, while rs4607615 is linked to Alzheimer’s disease. Thus, MRSA is implicated in both bipolar disorder and dementia.
The SH3PXD2A gene encodes TKS5, an isoform essential for proper mammalian development (89). Additionally, SH3PXD2A directly interacts with the ADAM metallopeptidase domain 15 gene, which is involved in neurodegeneration and inflammatory processes (90). SH3PXD2A is associated with brain white matter lesions and stroke (90–92). It is noteworthy that SH3PXD2A (rs17738042) is significantly associated with vascular dementia (50). Interestingly, rs3740473 of SH3PXD2A is associated with Alzheimer’s disease (93). The mechanism by which SH3PXD2A is linked to bipolar disorder remains unknown; however, a GWAS revealed a significant association between bipolar disorder and SH3PXD2A (31). Therefore, SH3PXD2A is a gene of interest in relation to bipolar disorder and dementia.
In addition, we previously reviewed that rs334558 of the GSK-3β gene was associated with depression, bipolar disorder, and dementia (16, 94–96). We hypothesized the existence of a mental GSK-3 disease, which comprises a specific group of patients associated with the GSK-3β variant, whose diagnoses longitudinally transition from depression to bipolar disorder and finally to dementia (16). Therefore, although we could not find a significant association between the GSK-3β gene and bipolar disorder and dementia in this GWAS review, rs334558 of the GSK-3β gene is associated with bipolar disorder and dementia.
This review has several limitations. First, it relies on GWAS, which are cross-sectional in nature, and examines bipolar disorder and dementia at each study time point. Therefore, genetic studies involving the longitudinal transitions from bipolar disorder to dementia or cognitive function decline in patients with bipolar disorder are needed. Hence, future longitudinal studies are needed to explore the genetic factors associated with cognitive decline in bipolar disorder and the onset of dementia. Second, bipolar disorder and dementia are believed to be associated with various genes, and it is difficult to explain them based solely on a single gene or SNP. Therefore, it is necessary to consider factors from multiple genes, such as polygenic scores, which can summarize global genomic risk rather than focusing on specific variants. Third, this review only examined whether the identified genes or SNPs were relevant by extracting them from individual studies and did not involve a combined GWAS analysis of the cases in each study. Finally, this review is qualitative, not quantitative, and weighs the effects of candidate genes.
Conclusion
In conclusion, CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A may be associated with the neuro-progression of bipolar disorder to dementia. Further genetic studies are needed to comprehensively clarify the role of genes in cognitive decline and dementia development in patients with bipolar disorder.
Statements
Author contributions
HH: Writing – original draft, Writing – review & editing. TT: Writing – review & editing.
Funding
The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The present work was supported by the Japanese Society for the Promotion of Science as Grant-in-Aid for Scientific Research (21K07502).
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.
The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision
The reviewer HH is currently organizing a Research Topic with the authors.
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Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1414776/full#supplementary-material
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Summary
Keywords
bipolar disorder, dementia, gene, single nucleotide polymorphisms, genome-wide association study
Citation
Hirakawa H and Terao T (2024) The genetic association between bipolar disorder and dementia: a qualitative review. Front. Psychiatry 15:1414776. doi: 10.3389/fpsyt.2024.1414776
Received
09 April 2024
Accepted
05 August 2024
Published
20 August 2024
Volume
15 - 2024
Edited by
Tasuku Hashimoto, International University of Health and Welfare (IUHW), Japan
Reviewed by
Hikaru Hori, Fukuoka University, Japan
Shinichiro Ochi, Ehime University, Japan
Updates
Copyright
© 2024 Hirakawa and Terao.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Hirofumi Hirakawa, hira-hiro@oita-u.ac.jp
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