As mentioned previously in the Section “Introduction,” it has been revealed that AD risk is linked with ZCWPW1, SORL1, SLC24A4, RIN3, PTK2B, PLD3, PICALM, NME8, MS4A6E, MS4A4E, MS4A4A, MEF2C, INPP5D, HLA-DRB4, HLA-DRB1, FERMT2, EPHA1, DSG2, CR1, CLU, CELF1, CD33, CD2AP, CASS4, BIN1, APOE, and ABCA7 in GWAS and meta-analyses (7–12). To recognize probable genes implicated in the regulation of age-related cognitive decline, a recent association study has analyzed whether SNPs within these 27 AD-associated genes are linked with cognitive aging as well as via complex gene–gene and gene–environment interactions in a cohort of older Taiwanese adults (n = 634) aged over 60 years (mean age: 64.2 years) from the Taiwan Biobank (18). In order to weigh cognitive functions, the mini-mental state examination (MMSE) method was administered for all participants (18). Lin et al. tested 588 SNPs, but only the CASS4-rs911159 SNP persisted significant for cognitive aging after Bonferroni correction (18). In addition, their analysis results suggested an association with 6 more SNPs in the AD-related genes, encompassing the SLC24A4-rs67063100, RIN3-rs1885747, PLD3-rs11672825, MEF2C-rs9293506, FERMT2-rs4901317, and EPHA1-rs10952552 SNPs (18). Lin et al. also displayed the gene–gene interactions among the SLC24A4-rs67063100, MEF2C-rs9293506, FERMT2-rs4901317, EPHA-rs10952552, and CASS4-rs911159 SNPs on cognitive aging by using the generalized multifactor dimensionality reduction (GMDR) approach (18). Furthermore, they disclosed the gene–environment interactions of the MEF2C-rs9293506 and SLC24A4-rs67063100 SNP with environmental factors including social support, physical activity, smoking status, and alcohol consumption on cognitive aging by using the GMDR approach (18).

Consistent with the findings by Lin et al. (18), two preceding GWAS studies (8, 10) have reported that the EPHA1 rs11767557 SNP may affect the vulnerability to AD. In addition, the FERMT2 rs17125944, MEF2C rs190982, and SLC24A4 rs10498633 SNPs were prone to AD in a meta-analysis study (12). Moreover, a whole-exome sequencing study pinpointed a rare rs145999145 (Val232Met) variant in the PLD3 gene was liable to AD (13). The PLD3 gene may play a central role in dealing with amyloid-beta precursor protein (13).

The CASS4 protein is proposed to better characterize the functions of cell growing, spreading, adhesion, and other activities (19). Moreover, it was speculated that CASS4 plays a vital part in the hallmarks of AD such as the amyloid precursor protein (APP) and Tau protein (20). More recent studies also indicated an association between AD and the CASS4 rs7274581, rs6024870, and rs16979934 SNPs (12, 21–23). In contrast, a replication study indicated that the CASS4 rs7274581 SNP did not affect the risk of AD in a Spanish population (24).

Gene–gene interaction study inferred that SLC24A4, MEF2C, FERMT2, EPHA1, and CASS4 synergistically raised the propensity of cognitive aging by using the GMDR approach (18). It was further speculated that these five genes are comprised in the relevant pathology and pathways (18). EPHA1 is implicated in regulating neurodevelopment (20). FERMT2 contributes to Tau neurotoxicity and cell adhesion (25). MEF2C may influence hippocampal synaptic connectivity and thereby mediate hippocampal-dependent memory and learning (26). SLC24A4, in the vicinity of the RIN3 gene, is linked with neurodevelopment (27) as well as Tau pathology and APP (28).

The APOE gene, located on chromosome 19q13.32, encodes a major protein which is crucial for the regular catabolism of triglyceride-rich lipoprotein constituents (29). Conducting a GWAS study with the longitudinal cognitive testing data such as memory and perceptual speed, De Jager et al. discovered that APOE was genome-wide significantly correlated with age-related cognitive decline (mean age: 72.0~80.8 years) (30). A meta-analysis of 77 studies (n = 40,942) also suggested that carriers of the APOE ɛ4 allele, which were linked with late-onset AD, performed worse on several domains of cognitive functions including overall global cognitive ability, episodic memory, and executive functioning (31). Further, the APOE rs405509 and APOE rs440446 SNPs were more likely to develop non-pathological cognitive aging, independent of APOE major isoforms, in a Finnish population (32). In contrast, a replication study indicated that the APOE gene did not affect the risk of age-related cognitive decline in older Taiwanese adults (18).

Another potential candidate gene such as BDNF was reported to be implicated in age-related cognitive decline among the elderly (33). The BDNF gene, encoding proteins of the nerve growth factor family, was demonstrated to alter cognitive deficits in healthy subjects (mean age: 72.7 years) for normal aging by using the mean Z-scores based on three cognitive domains including motor function, memory, and perceptual speed (34). Ward et al. also disclosed an interaction between APOE and BDNF that predicted a cognitive effect in healthy older adults (35).

The COMT gene, located on chromosome 22q11.21, is essential in the metabolic degradation of prefrontal dopamine (36). A functional COMT Val158Met polymorphism has been shown to contribute to individual differences in cognitive aging in Taiwanese (mean age: 78.7 years) and German (mean age: 64.9~65.3 years) populations using MMSE scores (36, 37). Based on a 4-year longitudinal study, Dixon et al. also revealed that the APOE and COMT genes are complementary biomarkers in normal cognitive aging and early MCI for older adults (38).

The CR1 gene encodes a protein that plays a role in cellular binding and immune complexes (14). A replication study reported that the rs6656401 SNP in the CR1 gene, which is one of the susceptibility loci for AD, was significantly associated with cognitive deficits (mean age: 75.5~84.4 years) for normal aging (in terms of global cognitive decline) as well as for pathological aging (in terms of global AD pathology) using the cognitive testing data such as memory and global cognition (14). A subsequent replication study also indicated that the rs4844609 SNP in the CR1 gene modulates episodic memory decline and an interaction between APOE and CR1 influences cognitive decline for normal aging and for pathological aging (39). In contrast, a replication study indicated that the CR1 gene did not affect the risk of age-related cognitive decline in older Taiwanese adults (18).

Circadian rhythms are instinctively recurring cycles that determine the timing of biological events such as energy metabolism, hormone release, and sleep–wake cycles (40). Additionally, dysregulation of circadian rhythms is characteristic of the natural process of ongoing aging and cognitive decline (40). The circadian rhythms are maintained and triggered by a composition of core circadian clock genes, which can be classified as vital genes on provoking circadian rhythms in specific cells (41).

Circadian clock genes, encompassing RORB, RORA, PER3, PER2, PER1, NR1D1, NPAS2, CRY2, CRY1, CLOCK, and ARNT, may be also involved in cognitive impairment (40, 41). To find out potential genes implicated in the regulation of age-related cognitive decline, a recent study analyzed whether the 11 aforementioned core circadian clock genes as well as complex gene–gene and gene–environment interactions contributed to cognitive aging in more than 634 elderly individuals (mean age: 64.2 years) in Taiwan (42). As a result, four SNPs, including the RORA-rs13329238, NPAS2-rs17655330, CLOCK-rs3749473, and RORB-rs10781247 SNPs individually and interactively alters the hazard of cognitive deficits in terms of MMSE scores for normal aging (42). Finally, environmental factors such as smoking status, alcohol consumption, social support, and physical activity also interacted with these SNPs in regulating the liability of age-related cognitive decline (42).

CLOCK encodes a protein which creates the ARNTL/CLOCK heterodimeric protein with ARNTL (43). In addition, rs1554483, 3111, and rs4580704 CLOCK SNPs influenced the tendency to AD in Chinese subjects (44–46). However, these results were not confirmed in different populations (42).

The RORA and RORB proteins create a family of nuclear hormone receptors (47). These two genes were reported to have a key part in a wide variety of regulations; for instance, cellular metabolism, circadian rhythm, embryonic development, immunity, and inflammatory responses (48, 49).

It should be noted that NPAS2 encodes transcription factors which are a component belonging to the basic helix-loop-helix family, and the ARNTL/NPAS2 and ARNTL/CLOCK heterodimeric proteins can bind to chromatin, bringing about the upregulation in gene expression for PER1, PER2, PER3, CRY1, and CRY2 (50). In this manner, products of these CRY1, CRY2, PER1, PER2, and PER3 genes build a complex that inhibits the action of the ARNTL-containing complexes and in turn forms a negative feedback loop (50).

To identify possible genes implicated in the process of age-related cognitive decline, a recent association study of the Taiwan Biobank has hypothesized that SNPs in insulin resistance-associated genes, including the PPARG, GCKR, and ADAMTS9 genes, might be associated with cognitive aging individually or collectively in a cohort of Taiwanese individuals (n = 547; age > 60 years; mean age: 64.1 years) (51). The results indicated that 4 SNPs (including rs9831846, rs4317088, rs9985304, and rs73832338) within ADAMTS9 were linked with MMSE scores (that is, cognitive aging) after performing Bonferroni correction (51). In addition, Lin et al. identified a SNP–SNP interaction between ADAMTS9-rs76346246 and ADAMTS9-rs9985304 that may influence cognitive aging by using the GMDR approach (51).

ADAMTS9 is demonstrated in the regulation of a wide variety of processes, such as the control of organ shape during growth, the inhibition of angiogenesis, and the cleavage of proteoglycans (51). Since one of the risk factors for cognitive aging and AD is insulin resistance, insulin resistance-related genes might be linked with cognitive aging (52, 53). Insulin abnormalities raise the uncertainty for neurodegenerative disorders including MCI, AD, and cognitive aging (54, 55). Insulin is also a fundamental factor for normal brain functioning. It should be noted that ADAMTS9 is associated with insulin resistance, insulin sensitivity, and type 2 diabetes (56, 57). There is growing evidence that the ADAMTS-9 protein might participate in the processes of brain disease states including spinal cord injury, ischemic stroke, and transient middle cerebral artery occlusion in animal studies (58–60). In accordance, a GWAS study has identified the ADAMTS9 rs6795735 SNP as a candidate biomarker for age-related macular degeneration, which commonly occurs in elder adults (61).

A growing body of evidence suggests that REST may be involved with AD and cognitive aging (62). A recent replication study has assessed whether REST SNPs are associated with cognitive aging as well as via SNP–SNP interactions for normal aging in elder Taiwanese subjects (n = 634; mean age: 64.2 years) (62). Their analysis results demonstrated that REST-rs1277306 was linked with cognitive aging, which was measured by MMSE scores (62). This prediction is further supported by evidence that the association remained significant for individuals without APOE ε4 allele after Bonferroni correction (62). On the other hand, the REST rs1277306 SNP was not a predicting factor for cognitive aging among individuals with at least one APOE ε4 allele (62). In addition, Lin et al. tracked down an SNP–SNP interaction between the REST rs1713985 and REST rs1277306 SNPs on cognitive aging by using the GMDR. The REST protein is indicated in the modulation of synaptic plasticity, ion channels, vesicular transport, axonal growth, and neuronal differentiation (63, 64). In addition, REST is associated with amyloid β-protein toxicity, protection from oxidative stress, AD pathology, MCI, brain aging, and slow hippocampal loss (65–67). Additionally, REST might act as both a primary protector against neurodegeneration and an essential repressor for normal neurogenesis (65–67). Although APOE is well-established regarding its major role in cognitive decline in elder adults (68, 69), the biologically synergistic effects between the APOE and REST genes on cognitive aging are still unknown. It was speculated that APOE and REST might involve in a comparable pathway relevant to cognitive aging (70). Consistent with the findings by Lin et al. (62), several other studies pinpointed an interaction of APOE with PSEN2 (71), PSEN1 (72), PICALM (70), and APP (71, 73) by using patient stratification based on APOE ε4 status.

Recent studies indicate that DNA methylation, one of main epigenetic mechanisms, plays a crucial role in cognitive aging (74, 75). DNA methylation involves the inclusion of a methyl group to the DNA molecule, especially when a cytosine is followed by a guanine (76). DNA methylation is regularly associated with reduced transcriptional activity and is triggered by a family of DNA methyl-transferase proteins (77). Using repeated measures of composite scores for annual cognitive testing, Chouliaras et al. investigated associations among common SNPs in genes modulating DNA methylation and cognitive aging. They found that the rs11887120 SNP in the DNMT3A gene was associated with annual decline in cognitive deficits for normal aging in a Dutch population (78). In contrast, this finding was not replicated in German subjects (79). DNMT3A, encoding a DNA methyltransferase, is located in the cytoplasm and nucleus in de novo methylation (80).

With longitudinal cognitive ability data, a GWAS study reported that the rs2075650 SNP in the TOMM40 gene, which is adjacent to the APOE gene, was significantly associated with age-related cognitive decline (mean age: 64.6~79.1 years) (81). After fine SNP mapping of the TOMM40/APOE region, both APOE rs429358 and TOMM40 rs11556505 were correlated with cognitive aging (81). Furthermore, SNPs within the TOMM40/APOE zone possessed a non-protein-coding regulatory and functional effect in a functional genomic analysis, indicating that the TOMM40/APOE zone may be linked with nonpathological cognitive aging (81). The TOMM40 gene, located on chromosome 19q13.32, encodes the mitochondrial outer membrane complex relevant to the channel-forming subunit of the translocase, which is indispensable for construction of protein precursors to mitochondria (82).

The DTNBP1 gene encodes a protein that plays a role in the biogenesis of organelle linked with lysosomes, platelet dense granules, and melanosomes (83). It has been suggested that the DTNBP1 gene modulates general cognitive abilities both in schizophrenia patients and in healthy subjects in Japanese (mean age: 34.1~39.2) and German (mean age: 24.8) populations (84–87). In addition, Burdick et al. found that the CTCTAC risk haplotype of 6 SNPs including rs909706, rs1018381, rs2619522, rs760761, rs2619528, and rs1011313 in the DTNBP1 gene was associated with general cognitive ability and cognitive decline in schizophrenia patients (84).

In a recent systems genetics study applying a genetically diverse population of mice, Neuner et al. pinpointed Hp1bp3 gene to be a novel modulator of cognitive aging (88). Their findings also confirmed that as compared to cognitively healthy individuals, levels of HP1BP3 protein were significantly decreased in the hippocampi of elderly subjects with cognitive impairment, suggesting that reduced expression of Hp1bp3 may contribute to cognitive aging in both mice and humans (88). The HP1BP3 gene is located on chromosome 1p36.12 and encodes a histone H1 related protein with non-redundant and specific roles vital for viability and gain in humans (89).

It is worth mentioning a potential gene called SRR although, to our knowledge, there are only animal studies but no population studies for this gene in cognitive aging. SRR encodes the serine racemase enzyme which converts L-serine to d-serine. d-serine is an endogenous co-agonist for N-methyl-D-aspartate receptors (90). The SRR rs408067 SNP, located in the promoter region, may affect the transcription activity of the SRR gene (91). Reduced SRR expression impaired hippocampal age-related cognitive function in an animal study, suggesting that the SRR-dependent pathway might be one possible target of the hippocampus-related cognitive decline in aging (92). Another expression profiling study reported that various genes that are associated with cognitive ability were influenced by the SRR mutation (93).